Re: Protecting Tokens from Any Analysis
I wouldn’t worry about performance with that setup. I just checked on a production system with 13 million docs in four shards, so 3+ million per shard. I searched on the most common term in the title field and got a response in 31 milliseconds. This was probably not cached, because the collection gets frequent updates and is getting limited public traffic. That will change on Monday. Make sure that you have more free RAM than the size of the index. Allow for the size of the JVM, OS, etc. Make sure you have plenty of CPU. After you have the RAM, CPU is the bottleneck. wunder Walter Underwood wun...@wunderwood.org http://observer.wunderwood.org/ (my blog) > On Oct 9, 2019, at 12:33 PM, David Hastings > wrote: > > yup. youre going to find solr is WAY more efficient than you think when it > comes to complex queries. > > On Wed, Oct 9, 2019 at 3:17 PM Audrey Lorberfeld - audrey.lorberf...@ibm.com > wrote: > >> True...I guess another rub here is that we're using the edismax parser, so >> all of our queries are inherently OR queries. So for a query like 'the ibm >> way', the search engine would have to: >> >> 1) retrieve a document list for: >> --> "ibm" (this list is probably 80% of the documents) >> --> "the" (this list is 100% of the english documents) >> -- >"way" >> 2) apply edismax parser >> --> foreach term >> --> --> foreach document in term >> --> --> --> score it >> >> So, it seems like it would take a toll on our system but maybe that's >> incorrect! (For reference, our corpus is ~5MM documents, multi-language, >> and we get ~80k-100k queries/day) >> >> Are you using edismax? >> >> -- >> Audrey Lorberfeld >> Data Scientist, w3 Search >> IBM >> audrey.lorberf...@ibm.com >> >> >> On 10/9/19, 3:11 PM, "David Hastings" >> wrote: >> >>if you have anything close to a decent server you wont notice it all. >> im >>at about 21 million documents, index varies between 450gb to 800gb >>depending on merges, and about 60k searches a day and stay sub second >> non >>stop, and this is on a single core/non cloud environment >> >>On Wed, Oct 9, 2019 at 2:55 PM Audrey Lorberfeld - >> audrey.lorberf...@ibm.com >> wrote: >> >>> Also, in terms of computational cost, it would seem that including >> most >>> terms/not having a stop ilst would take a toll on the system. For >> instance, >>> right now we have "ibm" as a stop word because it appears everywhere >> in our >>> corpus. If we did not include it in the stop words file, we would >> have to >>> retrieve every single document in our corpus and rank them. That's a >> high >>> computational cost, no? >>> >>> -- >>> Audrey Lorberfeld >>> Data Scientist, w3 Search >>> IBM >>> audrey.lorberf...@ibm.com >>> >>> >>> On 10/9/19, 2:31 PM, "Audrey Lorberfeld - audrey.lorberf...@ibm.com" >> < >>> audrey.lorberf...@ibm.com> wrote: >>> >>>Wow, thank you so much, everyone. This is all incredibly helpful >>> insight. >>> >>>So, would it be fair to say that the majority of you all do NOT >> use >>> stop words? >>> >>>-- >>>Audrey Lorberfeld >>>Data Scientist, w3 Search >>>IBM >>>audrey.lorberf...@ibm.com >>> >>> >>>On 10/9/19, 11:14 AM, "David Hastings" < >> hastings.recurs...@gmail.com> >>> wrote: >>> >>>However, with all that said, stopwords CAN be useful in some >>> situations. I >>>combine stopwords with the shingle factory to create >> "interesting >>> phrases" >>>(not really) that i use in "my more like this" needs. for >> example, >>>europe for vacation >>>europe on vacation >>>will create the shingle >>>europe_vacation >>>which i can then use to relate other documents that would be >> much >>>more similar in such regard, rather than just using the >>> "interesting words" >>>europe, vacation >>> >>>with stop words, the shingles would be >>>europe_for >>>for_vacation >>>and >>>europe_on >>>on_vacation >>> >>>just something to keep in mind, theres a lot of creative >> ways to >>> use >>>stopwords depending on your needs. i use the above for a >> VERY >>> basic ML >>>teacher and it works way better than using stopwords, >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>>On Wed, Oct 9, 2019 at 10:51 AM Erick Erickson < >>> erickerick...@gmail.com> >>>wrote: >>> The theory behind stopwords is that they are “safe” to >> remove >>> when calculating relevance, so we can squeeze every last bit of >>> usefulness out of very constrained hardware (think 64K of memory. Yes >>> kilobytes). We’ve come a long way since then and the necessity of removing >>> stopwords from the indexed tokens to conserve RAM and disk is much less >> relevant >>> than it used to be in “the bad old days” when the idea of stopwords was >>> invented. I’m not quite so confident as Alex
Re: Re: Re: Re: Re: Protecting Tokens from Any Analysis
yup. youre going to find solr is WAY more efficient than you think when it comes to complex queries. On Wed, Oct 9, 2019 at 3:17 PM Audrey Lorberfeld - audrey.lorberf...@ibm.com wrote: > True...I guess another rub here is that we're using the edismax parser, so > all of our queries are inherently OR queries. So for a query like 'the ibm > way', the search engine would have to: > > 1) retrieve a document list for: > --> "ibm" (this list is probably 80% of the documents) > --> "the" (this list is 100% of the english documents) > -- >"way" > 2) apply edismax parser > --> foreach term > --> --> foreach document in term > --> --> --> score it > > So, it seems like it would take a toll on our system but maybe that's > incorrect! (For reference, our corpus is ~5MM documents, multi-language, > and we get ~80k-100k queries/day) > > Are you using edismax? > > -- > Audrey Lorberfeld > Data Scientist, w3 Search > IBM > audrey.lorberf...@ibm.com > > > On 10/9/19, 3:11 PM, "David Hastings" > wrote: > > if you have anything close to a decent server you wont notice it all. > im > at about 21 million documents, index varies between 450gb to 800gb > depending on merges, and about 60k searches a day and stay sub second > non > stop, and this is on a single core/non cloud environment > > On Wed, Oct 9, 2019 at 2:55 PM Audrey Lorberfeld - > audrey.lorberf...@ibm.com > wrote: > > > Also, in terms of computational cost, it would seem that including > most > > terms/not having a stop ilst would take a toll on the system. For > instance, > > right now we have "ibm" as a stop word because it appears everywhere > in our > > corpus. If we did not include it in the stop words file, we would > have to > > retrieve every single document in our corpus and rank them. That's a > high > > computational cost, no? > > > > -- > > Audrey Lorberfeld > > Data Scientist, w3 Search > > IBM > > audrey.lorberf...@ibm.com > > > > > > On 10/9/19, 2:31 PM, "Audrey Lorberfeld - audrey.lorberf...@ibm.com" > < > > audrey.lorberf...@ibm.com> wrote: > > > > Wow, thank you so much, everyone. This is all incredibly helpful > > insight. > > > > So, would it be fair to say that the majority of you all do NOT > use > > stop words? > > > > -- > > Audrey Lorberfeld > > Data Scientist, w3 Search > > IBM > > audrey.lorberf...@ibm.com > > > > > > On 10/9/19, 11:14 AM, "David Hastings" < > hastings.recurs...@gmail.com> > > wrote: > > > > However, with all that said, stopwords CAN be useful in some > > situations. I > > combine stopwords with the shingle factory to create > "interesting > > phrases" > > (not really) that i use in "my more like this" needs. for > example, > > europe for vacation > > europe on vacation > > will create the shingle > > europe_vacation > > which i can then use to relate other documents that would be > much > > more similar in such regard, rather than just using the > > "interesting words" > > europe, vacation > > > > with stop words, the shingles would be > > europe_for > > for_vacation > > and > > europe_on > > on_vacation > > > > just something to keep in mind, theres a lot of creative > ways to > > use > > stopwords depending on your needs. i use the above for a > VERY > > basic ML > > teacher and it works way better than using stopwords, > > > > > > > > > > > > > > > > > > > > > > > > > > > > On Wed, Oct 9, 2019 at 10:51 AM Erick Erickson < > > erickerick...@gmail.com> > > wrote: > > > > > The theory behind stopwords is that they are “safe” to > remove > > when > > > calculating relevance, so we can squeeze every last bit of > > usefulness out > > > of very constrained hardware (think 64K of memory. Yes > > kilobytes). We’ve > > > come a long way since then and the necessity of removing > > stopwords from the > > > indexed tokens to conserve RAM and disk is much less > relevant > > than it used > > > to be in “the bad old days” when the idea of stopwords was > > invented. > > > > > > I’m not quite so confident as Alex that there is “no > benefit”, > > but I’ll > > > totally agree that you should remove stopwords only > _after_ you > > have some > > > evidence that removing them is A Good Thing in your > situation. > > > > > > And removing stopwords leads to some interesting corner > cases. > > Consider a > >
Re: Re: Re: Re: Re: Protecting Tokens from Any Analysis
True...I guess another rub here is that we're using the edismax parser, so all of our queries are inherently OR queries. So for a query like 'the ibm way', the search engine would have to: 1) retrieve a document list for: --> "ibm" (this list is probably 80% of the documents) --> "the" (this list is 100% of the english documents) -- >"way" 2) apply edismax parser --> foreach term --> --> foreach document in term --> --> --> score it So, it seems like it would take a toll on our system but maybe that's incorrect! (For reference, our corpus is ~5MM documents, multi-language, and we get ~80k-100k queries/day) Are you using edismax? -- Audrey Lorberfeld Data Scientist, w3 Search IBM audrey.lorberf...@ibm.com On 10/9/19, 3:11 PM, "David Hastings" wrote: if you have anything close to a decent server you wont notice it all. im at about 21 million documents, index varies between 450gb to 800gb depending on merges, and about 60k searches a day and stay sub second non stop, and this is on a single core/non cloud environment On Wed, Oct 9, 2019 at 2:55 PM Audrey Lorberfeld - audrey.lorberf...@ibm.com wrote: > Also, in terms of computational cost, it would seem that including most > terms/not having a stop ilst would take a toll on the system. For instance, > right now we have "ibm" as a stop word because it appears everywhere in our > corpus. If we did not include it in the stop words file, we would have to > retrieve every single document in our corpus and rank them. That's a high > computational cost, no? > > -- > Audrey Lorberfeld > Data Scientist, w3 Search > IBM > audrey.lorberf...@ibm.com > > > On 10/9/19, 2:31 PM, "Audrey Lorberfeld - audrey.lorberf...@ibm.com" < > audrey.lorberf...@ibm.com> wrote: > > Wow, thank you so much, everyone. This is all incredibly helpful > insight. > > So, would it be fair to say that the majority of you all do NOT use > stop words? > > -- > Audrey Lorberfeld > Data Scientist, w3 Search > IBM > audrey.lorberf...@ibm.com > > > On 10/9/19, 11:14 AM, "David Hastings" > wrote: > > However, with all that said, stopwords CAN be useful in some > situations. I > combine stopwords with the shingle factory to create "interesting > phrases" > (not really) that i use in "my more like this" needs. for example, > europe for vacation > europe on vacation > will create the shingle > europe_vacation > which i can then use to relate other documents that would be much > more similar in such regard, rather than just using the > "interesting words" > europe, vacation > > with stop words, the shingles would be > europe_for > for_vacation > and > europe_on > on_vacation > > just something to keep in mind, theres a lot of creative ways to > use > stopwords depending on your needs. i use the above for a VERY > basic ML > teacher and it works way better than using stopwords, > > > > > > > > > > > > > > On Wed, Oct 9, 2019 at 10:51 AM Erick Erickson < > erickerick...@gmail.com> > wrote: > > > The theory behind stopwords is that they are “safe” to remove > when > > calculating relevance, so we can squeeze every last bit of > usefulness out > > of very constrained hardware (think 64K of memory. Yes > kilobytes). We’ve > > come a long way since then and the necessity of removing > stopwords from the > > indexed tokens to conserve RAM and disk is much less relevant > than it used > > to be in “the bad old days” when the idea of stopwords was > invented. > > > > I’m not quite so confident as Alex that there is “no benefit”, > but I’ll > > totally agree that you should remove stopwords only _after_ you > have some > > evidence that removing them is A Good Thing in your situation. > > > > And removing stopwords leads to some interesting corner cases. > Consider a > > search for “to be or not to be” if they’re all stopwords. > > > > Best, > > Erick > > > > > On Oct 9, 2019, at 9:38 AM, Audrey Lorberfeld - > > audrey.lorberf...@ibm.com wrote: > > > > > > Hey Alex, > > > > > > Thank you! > > > > > > Re: stopwords being a thing of the past due to the > affordability of > > hardware...can you expand?
Re: Re: Re: Re: Protecting Tokens from Any Analysis
if you have anything close to a decent server you wont notice it all. im at about 21 million documents, index varies between 450gb to 800gb depending on merges, and about 60k searches a day and stay sub second non stop, and this is on a single core/non cloud environment On Wed, Oct 9, 2019 at 2:55 PM Audrey Lorberfeld - audrey.lorberf...@ibm.com wrote: > Also, in terms of computational cost, it would seem that including most > terms/not having a stop ilst would take a toll on the system. For instance, > right now we have "ibm" as a stop word because it appears everywhere in our > corpus. If we did not include it in the stop words file, we would have to > retrieve every single document in our corpus and rank them. That's a high > computational cost, no? > > -- > Audrey Lorberfeld > Data Scientist, w3 Search > IBM > audrey.lorberf...@ibm.com > > > On 10/9/19, 2:31 PM, "Audrey Lorberfeld - audrey.lorberf...@ibm.com" < > audrey.lorberf...@ibm.com> wrote: > > Wow, thank you so much, everyone. This is all incredibly helpful > insight. > > So, would it be fair to say that the majority of you all do NOT use > stop words? > > -- > Audrey Lorberfeld > Data Scientist, w3 Search > IBM > audrey.lorberf...@ibm.com > > > On 10/9/19, 11:14 AM, "David Hastings" > wrote: > > However, with all that said, stopwords CAN be useful in some > situations. I > combine stopwords with the shingle factory to create "interesting > phrases" > (not really) that i use in "my more like this" needs. for example, > europe for vacation > europe on vacation > will create the shingle > europe_vacation > which i can then use to relate other documents that would be much > more similar in such regard, rather than just using the > "interesting words" > europe, vacation > > with stop words, the shingles would be > europe_for > for_vacation > and > europe_on > on_vacation > > just something to keep in mind, theres a lot of creative ways to > use > stopwords depending on your needs. i use the above for a VERY > basic ML > teacher and it works way better than using stopwords, > > > > > > > > > > > > > > On Wed, Oct 9, 2019 at 10:51 AM Erick Erickson < > erickerick...@gmail.com> > wrote: > > > The theory behind stopwords is that they are “safe” to remove > when > > calculating relevance, so we can squeeze every last bit of > usefulness out > > of very constrained hardware (think 64K of memory. Yes > kilobytes). We’ve > > come a long way since then and the necessity of removing > stopwords from the > > indexed tokens to conserve RAM and disk is much less relevant > than it used > > to be in “the bad old days” when the idea of stopwords was > invented. > > > > I’m not quite so confident as Alex that there is “no benefit”, > but I’ll > > totally agree that you should remove stopwords only _after_ you > have some > > evidence that removing them is A Good Thing in your situation. > > > > And removing stopwords leads to some interesting corner cases. > Consider a > > search for “to be or not to be” if they’re all stopwords. > > > > Best, > > Erick > > > > > On Oct 9, 2019, at 9:38 AM, Audrey Lorberfeld - > > audrey.lorberf...@ibm.com wrote: > > > > > > Hey Alex, > > > > > > Thank you! > > > > > > Re: stopwords being a thing of the past due to the > affordability of > > hardware...can you expand? I'm not sure I understand. > > > > > > -- > > > Audrey Lorberfeld > > > Data Scientist, w3 Search > > > IBM > > > audrey.lorberf...@ibm.com > > > > > > > > > On 10/8/19, 1:01 PM, "David Hastings" < > hastings.recurs...@gmail.com> > > wrote: > > > > > >Another thing to add to the above, > > >> > > >> IT:ibm. In this case, we would want to maintain the colon and > the > > >> capitalization (otherwise “it” would be taken out as a > stopword). > > >> > > >stopwords are a thing of the past at this point. there is > no benefit > > to > > >using them now with hardware being so cheap. > > > > > >On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch < > > arafa...@gmail.com> > > >wrote: > > > > > >> If you don't want it to be touched by a tokenizer, how would > the > > >> protection step know that the sequence of characters you want > to > > >> protect is "IT:ibm" and not "this is an IT:ibm term I want to > > >> protect"? > > >> > > >> What it sounds to me is that you may want to: > > >> 1) copyField
Re: Re: Re: Protecting Tokens from Any Analysis
only in my more like this tools, but they have a very specific purpose, otherwise no On Wed, Oct 9, 2019 at 2:31 PM Audrey Lorberfeld - audrey.lorberf...@ibm.com wrote: > Wow, thank you so much, everyone. This is all incredibly helpful insight. > > So, would it be fair to say that the majority of you all do NOT use stop > words? > > -- > Audrey Lorberfeld > Data Scientist, w3 Search > IBM > audrey.lorberf...@ibm.com > > > On 10/9/19, 11:14 AM, "David Hastings" > wrote: > > However, with all that said, stopwords CAN be useful in some > situations. I > combine stopwords with the shingle factory to create "interesting > phrases" > (not really) that i use in "my more like this" needs. for example, > europe for vacation > europe on vacation > will create the shingle > europe_vacation > which i can then use to relate other documents that would be much > more similar in such regard, rather than just using the "interesting > words" > europe, vacation > > with stop words, the shingles would be > europe_for > for_vacation > and > europe_on > on_vacation > > just something to keep in mind, theres a lot of creative ways to use > stopwords depending on your needs. i use the above for a VERY basic ML > teacher and it works way better than using stopwords, > > > > > > > > > > > > > > On Wed, Oct 9, 2019 at 10:51 AM Erick Erickson < > erickerick...@gmail.com> > wrote: > > > The theory behind stopwords is that they are “safe” to remove when > > calculating relevance, so we can squeeze every last bit of > usefulness out > > of very constrained hardware (think 64K of memory. Yes kilobytes). > We’ve > > come a long way since then and the necessity of removing stopwords > from the > > indexed tokens to conserve RAM and disk is much less relevant than > it used > > to be in “the bad old days” when the idea of stopwords was invented. > > > > I’m not quite so confident as Alex that there is “no benefit”, but > I’ll > > totally agree that you should remove stopwords only _after_ you have > some > > evidence that removing them is A Good Thing in your situation. > > > > And removing stopwords leads to some interesting corner cases. > Consider a > > search for “to be or not to be” if they’re all stopwords. > > > > Best, > > Erick > > > > > On Oct 9, 2019, at 9:38 AM, Audrey Lorberfeld - > > audrey.lorberf...@ibm.com wrote: > > > > > > Hey Alex, > > > > > > Thank you! > > > > > > Re: stopwords being a thing of the past due to the affordability of > > hardware...can you expand? I'm not sure I understand. > > > > > > -- > > > Audrey Lorberfeld > > > Data Scientist, w3 Search > > > IBM > > > audrey.lorberf...@ibm.com > > > > > > > > > On 10/8/19, 1:01 PM, "David Hastings" < > hastings.recurs...@gmail.com> > > wrote: > > > > > >Another thing to add to the above, > > >> > > >> IT:ibm. In this case, we would want to maintain the colon and the > > >> capitalization (otherwise “it” would be taken out as a stopword). > > >> > > >stopwords are a thing of the past at this point. there is no > benefit > > to > > >using them now with hardware being so cheap. > > > > > >On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch < > > arafa...@gmail.com> > > >wrote: > > > > > >> If you don't want it to be touched by a tokenizer, how would the > > >> protection step know that the sequence of characters you want to > > >> protect is "IT:ibm" and not "this is an IT:ibm term I want to > > >> protect"? > > >> > > >> What it sounds to me is that you may want to: > > >> 1) copyField to a second field > > >> 2) Apply a much lighter (whitespace?) tokenizer to that second > field > > >> 3) Run the results through something like KeepWordFilterFactory > > >> 4) Search both fields with a boost on the second, higher-signal > field > > >> > > >> The other option is to run CharacterFilter, > > >> (PatternReplaceCharFilterFactory) which is pre-tokenizer to map > known > > >> complex acronyms to non-tokenizable substitutions. E.g. "IT:ibm -> > > >> term365". As long as it is done on both indexing and query, they > will > > >> still match. You may have to have a bunch of them or write some > sort > > >> of lookup map. > > >> > > >> Regards, > > >> Alex. > > >> > > >> On Tue, 8 Oct 2019 at 12:10, Audrey Lorberfeld - > > >> audrey.lorberf...@ibm.com wrote: > > >>> > > >>> Hi All, > > >>> > > >>> This is likely a rudimentary question, but I can’t seem to find a > > >> straight-forward answer on forums or the documentation…is there a > way to > > >> protect tokens from ANY analysis? I know things like the > > >> KeywordMarkerFilterFactory protect
Re: Re: Re: Re: Protecting Tokens from Any Analysis
oh and by 'non stop' i mean close enough for me :) On Wed, Oct 9, 2019 at 2:59 PM David Hastings wrote: > if you have anything close to a decent server you wont notice it all. im > at about 21 million documents, index varies between 450gb to 800gb > depending on merges, and about 60k searches a day and stay sub second non > stop, and this is on a single core/non cloud environment > > On Wed, Oct 9, 2019 at 2:55 PM Audrey Lorberfeld - > audrey.lorberf...@ibm.com wrote: > >> Also, in terms of computational cost, it would seem that including most >> terms/not having a stop ilst would take a toll on the system. For instance, >> right now we have "ibm" as a stop word because it appears everywhere in our >> corpus. If we did not include it in the stop words file, we would have to >> retrieve every single document in our corpus and rank them. That's a high >> computational cost, no? >> >> -- >> Audrey Lorberfeld >> Data Scientist, w3 Search >> IBM >> audrey.lorberf...@ibm.com >> >> >> On 10/9/19, 2:31 PM, "Audrey Lorberfeld - audrey.lorberf...@ibm.com" < >> audrey.lorberf...@ibm.com> wrote: >> >> Wow, thank you so much, everyone. This is all incredibly helpful >> insight. >> >> So, would it be fair to say that the majority of you all do NOT use >> stop words? >> >> -- >> Audrey Lorberfeld >> Data Scientist, w3 Search >> IBM >> audrey.lorberf...@ibm.com >> >> >> On 10/9/19, 11:14 AM, "David Hastings" >> wrote: >> >> However, with all that said, stopwords CAN be useful in some >> situations. I >> combine stopwords with the shingle factory to create "interesting >> phrases" >> (not really) that i use in "my more like this" needs. for >> example, >> europe for vacation >> europe on vacation >> will create the shingle >> europe_vacation >> which i can then use to relate other documents that would be much >> more similar in such regard, rather than just using the >> "interesting words" >> europe, vacation >> >> with stop words, the shingles would be >> europe_for >> for_vacation >> and >> europe_on >> on_vacation >> >> just something to keep in mind, theres a lot of creative ways to >> use >> stopwords depending on your needs. i use the above for a VERY >> basic ML >> teacher and it works way better than using stopwords, >> >> >> >> >> >> >> >> >> >> >> >> >> >> On Wed, Oct 9, 2019 at 10:51 AM Erick Erickson < >> erickerick...@gmail.com> >> wrote: >> >> > The theory behind stopwords is that they are “safe” to remove >> when >> > calculating relevance, so we can squeeze every last bit of >> usefulness out >> > of very constrained hardware (think 64K of memory. Yes >> kilobytes). We’ve >> > come a long way since then and the necessity of removing >> stopwords from the >> > indexed tokens to conserve RAM and disk is much less relevant >> than it used >> > to be in “the bad old days” when the idea of stopwords was >> invented. >> > >> > I’m not quite so confident as Alex that there is “no benefit”, >> but I’ll >> > totally agree that you should remove stopwords only _after_ you >> have some >> > evidence that removing them is A Good Thing in your situation. >> > >> > And removing stopwords leads to some interesting corner cases. >> Consider a >> > search for “to be or not to be” if they’re all stopwords. >> > >> > Best, >> > Erick >> > >> > > On Oct 9, 2019, at 9:38 AM, Audrey Lorberfeld - >> > audrey.lorberf...@ibm.com wrote: >> > > >> > > Hey Alex, >> > > >> > > Thank you! >> > > >> > > Re: stopwords being a thing of the past due to the >> affordability of >> > hardware...can you expand? I'm not sure I understand. >> > > >> > > -- >> > > Audrey Lorberfeld >> > > Data Scientist, w3 Search >> > > IBM >> > > audrey.lorberf...@ibm.com >> > > >> > > >> > > On 10/8/19, 1:01 PM, "David Hastings" < >> hastings.recurs...@gmail.com> >> > wrote: >> > > >> > >Another thing to add to the above, >> > >> >> > >> IT:ibm. In this case, we would want to maintain the colon >> and the >> > >> capitalization (otherwise “it” would be taken out as a >> stopword). >> > >> >> > >stopwords are a thing of the past at this point. there is >> no benefit >> > to >> > >using them now with hardware being so cheap. >> > > >> > >On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch < >> > arafa...@gmail.com> >> > >wrote: >> > > >> > >> If you don't want it to be touched by a tokenizer, how would >> the >> > >>
Re: Re: Re: Re: Protecting Tokens from Any Analysis
Also, in terms of computational cost, it would seem that including most terms/not having a stop ilst would take a toll on the system. For instance, right now we have "ibm" as a stop word because it appears everywhere in our corpus. If we did not include it in the stop words file, we would have to retrieve every single document in our corpus and rank them. That's a high computational cost, no? -- Audrey Lorberfeld Data Scientist, w3 Search IBM audrey.lorberf...@ibm.com On 10/9/19, 2:31 PM, "Audrey Lorberfeld - audrey.lorberf...@ibm.com" wrote: Wow, thank you so much, everyone. This is all incredibly helpful insight. So, would it be fair to say that the majority of you all do NOT use stop words? -- Audrey Lorberfeld Data Scientist, w3 Search IBM audrey.lorberf...@ibm.com On 10/9/19, 11:14 AM, "David Hastings" wrote: However, with all that said, stopwords CAN be useful in some situations. I combine stopwords with the shingle factory to create "interesting phrases" (not really) that i use in "my more like this" needs. for example, europe for vacation europe on vacation will create the shingle europe_vacation which i can then use to relate other documents that would be much more similar in such regard, rather than just using the "interesting words" europe, vacation with stop words, the shingles would be europe_for for_vacation and europe_on on_vacation just something to keep in mind, theres a lot of creative ways to use stopwords depending on your needs. i use the above for a VERY basic ML teacher and it works way better than using stopwords, On Wed, Oct 9, 2019 at 10:51 AM Erick Erickson wrote: > The theory behind stopwords is that they are “safe” to remove when > calculating relevance, so we can squeeze every last bit of usefulness out > of very constrained hardware (think 64K of memory. Yes kilobytes). We’ve > come a long way since then and the necessity of removing stopwords from the > indexed tokens to conserve RAM and disk is much less relevant than it used > to be in “the bad old days” when the idea of stopwords was invented. > > I’m not quite so confident as Alex that there is “no benefit”, but I’ll > totally agree that you should remove stopwords only _after_ you have some > evidence that removing them is A Good Thing in your situation. > > And removing stopwords leads to some interesting corner cases. Consider a > search for “to be or not to be” if they’re all stopwords. > > Best, > Erick > > > On Oct 9, 2019, at 9:38 AM, Audrey Lorberfeld - > audrey.lorberf...@ibm.com wrote: > > > > Hey Alex, > > > > Thank you! > > > > Re: stopwords being a thing of the past due to the affordability of > hardware...can you expand? I'm not sure I understand. > > > > -- > > Audrey Lorberfeld > > Data Scientist, w3 Search > > IBM > > audrey.lorberf...@ibm.com > > > > > > On 10/8/19, 1:01 PM, "David Hastings" > wrote: > > > >Another thing to add to the above, > >> > >> IT:ibm. In this case, we would want to maintain the colon and the > >> capitalization (otherwise “it” would be taken out as a stopword). > >> > >stopwords are a thing of the past at this point. there is no benefit > to > >using them now with hardware being so cheap. > > > >On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch < > arafa...@gmail.com> > >wrote: > > > >> If you don't want it to be touched by a tokenizer, how would the > >> protection step know that the sequence of characters you want to > >> protect is "IT:ibm" and not "this is an IT:ibm term I want to > >> protect"? > >> > >> What it sounds to me is that you may want to: > >> 1) copyField to a second field > >> 2) Apply a much lighter (whitespace?) tokenizer to that second field > >> 3) Run the results through something like KeepWordFilterFactory > >> 4) Search both fields with a boost on the second, higher-signal field > >> > >> The other option is to run CharacterFilter, > >> (PatternReplaceCharFilterFactory) which is pre-tokenizer to map known > >> complex acronyms to non-tokenizable substitutions. E.g. "IT:ibm -> > >> term365". As long as it is done on
Re: Protecting Tokens from Any Analysis
Yeah, I dont use it as a search, only well, finding more documents like that one :) . for my purposes i tested between 2 to 5 part shingles and ended up that the 2 part was actually giving me better results, for my use case, than using any more. I dont suppose you could point me to any of the phrase IDF documentation for solr by chance? That would be fun to poke around with. On Wed, Oct 9, 2019 at 2:49 PM Walter Underwood wrote: > We did something like that with Infoseek and Ultraseek. We had a set of > “glue words” that made noun phrases and indexed patterns like “noun glue > noun” > as single tokens. > > I remember Doug Cutting saying that Nutch did something similar using > pairs, > but using that as a prefilter instead of as a relevance term. > > This is a way to get phrase IDF, which is pretty powerful stuff. Infoseek > always > beat Google in relevance tests, probably because of phrase IDF. > > More Like This could do the same thing, but it seems to be really slow and > not especially useful as a search component. > > wunder > Walter Underwood > wun...@wunderwood.org > http://observer.wunderwood.org/ (my blog) > > > On Oct 9, 2019, at 8:14 AM, David Hastings > wrote: > > > > However, with all that said, stopwords CAN be useful in some > situations. I > > combine stopwords with the shingle factory to create "interesting > phrases" > > (not really) that i use in "my more like this" needs. for example, > > europe for vacation > > europe on vacation > > will create the shingle > > europe_vacation > > which i can then use to relate other documents that would be much > > more similar in such regard, rather than just using the "interesting > words" > > europe, vacation > > > > with stop words, the shingles would be > > europe_for > > for_vacation > > and > > europe_on > > on_vacation > > > > just something to keep in mind, theres a lot of creative ways to use > > stopwords depending on your needs. i use the above for a VERY basic ML > > teacher and it works way better than using stopwords, > > > > On Wed, Oct 9, 2019 at 10:51 AM Erick Erickson > > wrote: > > > >> The theory behind stopwords is that they are “safe” to remove when > >> calculating relevance, so we can squeeze every last bit of usefulness > out > >> of very constrained hardware (think 64K of memory. Yes kilobytes). We’ve > >> come a long way since then and the necessity of removing stopwords from > the > >> indexed tokens to conserve RAM and disk is much less relevant than it > used > >> to be in “the bad old days” when the idea of stopwords was invented. > >> > >> I’m not quite so confident as Alex that there is “no benefit”, but I’ll > >> totally agree that you should remove stopwords only _after_ you have > some > >> evidence that removing them is A Good Thing in your situation. > >> > >> And removing stopwords leads to some interesting corner cases. Consider > a > >> search for “to be or not to be” if they’re all stopwords. > >> > >> Best, > >> Erick > >> > >>> On Oct 9, 2019, at 9:38 AM, Audrey Lorberfeld - > >> audrey.lorberf...@ibm.com wrote: > >>> > >>> Hey Alex, > >>> > >>> Thank you! > >>> > >>> Re: stopwords being a thing of the past due to the affordability of > >> hardware...can you expand? I'm not sure I understand. > >>> > >>> -- > >>> Audrey Lorberfeld > >>> Data Scientist, w3 Search > >>> IBM > >>> audrey.lorberf...@ibm.com > >>> > >>> > >>> On 10/8/19, 1:01 PM, "David Hastings" > >> wrote: > >>> > >>> Another thing to add to the above, > > IT:ibm. In this case, we would want to maintain the colon and the > capitalization (otherwise “it” would be taken out as a stopword). > > >>> stopwords are a thing of the past at this point. there is no benefit > >> to > >>> using them now with hardware being so cheap. > >>> > >>> On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch < > >> arafa...@gmail.com> > >>> wrote: > >>> > If you don't want it to be touched by a tokenizer, how would the > protection step know that the sequence of characters you want to > protect is "IT:ibm" and not "this is an IT:ibm term I want to > protect"? > > What it sounds to me is that you may want to: > 1) copyField to a second field > 2) Apply a much lighter (whitespace?) tokenizer to that second field > 3) Run the results through something like KeepWordFilterFactory > 4) Search both fields with a boost on the second, higher-signal field > > The other option is to run CharacterFilter, > (PatternReplaceCharFilterFactory) which is pre-tokenizer to map known > complex acronyms to non-tokenizable substitutions. E.g. "IT:ibm -> > term365". As long as it is done on both indexing and query, they will > still match. You may have to have a bunch of them or write some sort > of lookup map. > > Regards, > Alex. > > On Tue, 8 Oct 2019 at 12:10, Audrey Lorberfeld - > audrey.lorberf...@ibm.com wrote: > > >
Re: Protecting Tokens from Any Analysis
We did something like that with Infoseek and Ultraseek. We had a set of “glue words” that made noun phrases and indexed patterns like “noun glue noun” as single tokens. I remember Doug Cutting saying that Nutch did something similar using pairs, but using that as a prefilter instead of as a relevance term. This is a way to get phrase IDF, which is pretty powerful stuff. Infoseek always beat Google in relevance tests, probably because of phrase IDF. More Like This could do the same thing, but it seems to be really slow and not especially useful as a search component. wunder Walter Underwood wun...@wunderwood.org http://observer.wunderwood.org/ (my blog) > On Oct 9, 2019, at 8:14 AM, David Hastings > wrote: > > However, with all that said, stopwords CAN be useful in some situations. I > combine stopwords with the shingle factory to create "interesting phrases" > (not really) that i use in "my more like this" needs. for example, > europe for vacation > europe on vacation > will create the shingle > europe_vacation > which i can then use to relate other documents that would be much > more similar in such regard, rather than just using the "interesting words" > europe, vacation > > with stop words, the shingles would be > europe_for > for_vacation > and > europe_on > on_vacation > > just something to keep in mind, theres a lot of creative ways to use > stopwords depending on your needs. i use the above for a VERY basic ML > teacher and it works way better than using stopwords, > > On Wed, Oct 9, 2019 at 10:51 AM Erick Erickson > wrote: > >> The theory behind stopwords is that they are “safe” to remove when >> calculating relevance, so we can squeeze every last bit of usefulness out >> of very constrained hardware (think 64K of memory. Yes kilobytes). We’ve >> come a long way since then and the necessity of removing stopwords from the >> indexed tokens to conserve RAM and disk is much less relevant than it used >> to be in “the bad old days” when the idea of stopwords was invented. >> >> I’m not quite so confident as Alex that there is “no benefit”, but I’ll >> totally agree that you should remove stopwords only _after_ you have some >> evidence that removing them is A Good Thing in your situation. >> >> And removing stopwords leads to some interesting corner cases. Consider a >> search for “to be or not to be” if they’re all stopwords. >> >> Best, >> Erick >> >>> On Oct 9, 2019, at 9:38 AM, Audrey Lorberfeld - >> audrey.lorberf...@ibm.com wrote: >>> >>> Hey Alex, >>> >>> Thank you! >>> >>> Re: stopwords being a thing of the past due to the affordability of >> hardware...can you expand? I'm not sure I understand. >>> >>> -- >>> Audrey Lorberfeld >>> Data Scientist, w3 Search >>> IBM >>> audrey.lorberf...@ibm.com >>> >>> >>> On 10/8/19, 1:01 PM, "David Hastings" >> wrote: >>> >>> Another thing to add to the above, IT:ibm. In this case, we would want to maintain the colon and the capitalization (otherwise “it” would be taken out as a stopword). >>> stopwords are a thing of the past at this point. there is no benefit >> to >>> using them now with hardware being so cheap. >>> >>> On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch < >> arafa...@gmail.com> >>> wrote: >>> If you don't want it to be touched by a tokenizer, how would the protection step know that the sequence of characters you want to protect is "IT:ibm" and not "this is an IT:ibm term I want to protect"? What it sounds to me is that you may want to: 1) copyField to a second field 2) Apply a much lighter (whitespace?) tokenizer to that second field 3) Run the results through something like KeepWordFilterFactory 4) Search both fields with a boost on the second, higher-signal field The other option is to run CharacterFilter, (PatternReplaceCharFilterFactory) which is pre-tokenizer to map known complex acronyms to non-tokenizable substitutions. E.g. "IT:ibm -> term365". As long as it is done on both indexing and query, they will still match. You may have to have a bunch of them or write some sort of lookup map. Regards, Alex. On Tue, 8 Oct 2019 at 12:10, Audrey Lorberfeld - audrey.lorberf...@ibm.com wrote: > > Hi All, > > This is likely a rudimentary question, but I can’t seem to find a straight-forward answer on forums or the documentation…is there a way to protect tokens from ANY analysis? I know things like the KeywordMarkerFilterFactory protect tokens from stemming, but we have >> some terms we don’t even want our tokenizer to touch. Mostly, these are IBM-specific acronyms, such as IT:ibm. In this case, we would want to maintain the colon and the capitalization (otherwise “it” would be taken out as a stopword). > > Any advice is appreciated! > > Thank you, > Audrey > > -- >
Re: Re: Re: Protecting Tokens from Any Analysis
Wow, thank you so much, everyone. This is all incredibly helpful insight. So, would it be fair to say that the majority of you all do NOT use stop words? -- Audrey Lorberfeld Data Scientist, w3 Search IBM audrey.lorberf...@ibm.com On 10/9/19, 11:14 AM, "David Hastings" wrote: However, with all that said, stopwords CAN be useful in some situations. I combine stopwords with the shingle factory to create "interesting phrases" (not really) that i use in "my more like this" needs. for example, europe for vacation europe on vacation will create the shingle europe_vacation which i can then use to relate other documents that would be much more similar in such regard, rather than just using the "interesting words" europe, vacation with stop words, the shingles would be europe_for for_vacation and europe_on on_vacation just something to keep in mind, theres a lot of creative ways to use stopwords depending on your needs. i use the above for a VERY basic ML teacher and it works way better than using stopwords, On Wed, Oct 9, 2019 at 10:51 AM Erick Erickson wrote: > The theory behind stopwords is that they are “safe” to remove when > calculating relevance, so we can squeeze every last bit of usefulness out > of very constrained hardware (think 64K of memory. Yes kilobytes). We’ve > come a long way since then and the necessity of removing stopwords from the > indexed tokens to conserve RAM and disk is much less relevant than it used > to be in “the bad old days” when the idea of stopwords was invented. > > I’m not quite so confident as Alex that there is “no benefit”, but I’ll > totally agree that you should remove stopwords only _after_ you have some > evidence that removing them is A Good Thing in your situation. > > And removing stopwords leads to some interesting corner cases. Consider a > search for “to be or not to be” if they’re all stopwords. > > Best, > Erick > > > On Oct 9, 2019, at 9:38 AM, Audrey Lorberfeld - > audrey.lorberf...@ibm.com wrote: > > > > Hey Alex, > > > > Thank you! > > > > Re: stopwords being a thing of the past due to the affordability of > hardware...can you expand? I'm not sure I understand. > > > > -- > > Audrey Lorberfeld > > Data Scientist, w3 Search > > IBM > > audrey.lorberf...@ibm.com > > > > > > On 10/8/19, 1:01 PM, "David Hastings" > wrote: > > > >Another thing to add to the above, > >> > >> IT:ibm. In this case, we would want to maintain the colon and the > >> capitalization (otherwise “it” would be taken out as a stopword). > >> > >stopwords are a thing of the past at this point. there is no benefit > to > >using them now with hardware being so cheap. > > > >On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch < > arafa...@gmail.com> > >wrote: > > > >> If you don't want it to be touched by a tokenizer, how would the > >> protection step know that the sequence of characters you want to > >> protect is "IT:ibm" and not "this is an IT:ibm term I want to > >> protect"? > >> > >> What it sounds to me is that you may want to: > >> 1) copyField to a second field > >> 2) Apply a much lighter (whitespace?) tokenizer to that second field > >> 3) Run the results through something like KeepWordFilterFactory > >> 4) Search both fields with a boost on the second, higher-signal field > >> > >> The other option is to run CharacterFilter, > >> (PatternReplaceCharFilterFactory) which is pre-tokenizer to map known > >> complex acronyms to non-tokenizable substitutions. E.g. "IT:ibm -> > >> term365". As long as it is done on both indexing and query, they will > >> still match. You may have to have a bunch of them or write some sort > >> of lookup map. > >> > >> Regards, > >> Alex. > >> > >> On Tue, 8 Oct 2019 at 12:10, Audrey Lorberfeld - > >> audrey.lorberf...@ibm.com wrote: > >>> > >>> Hi All, > >>> > >>> This is likely a rudimentary question, but I can’t seem to find a > >> straight-forward answer on forums or the documentation…is there a way to > >> protect tokens from ANY analysis? I know things like the > >> KeywordMarkerFilterFactory protect tokens from stemming, but we have > some > >> terms we don’t even want our tokenizer to touch. Mostly, these are > >> IBM-specific acronyms, such as IT:ibm. In this case, we would want to > >> maintain the colon and the capitalization (otherwise “it” would be taken > >> out as a stopword). > >>> > >>> Any advice is appreciated! > >>> > >>> Thank you, > >>> Audrey > >>> > >>> -- > >>>
Re: Re: Protecting Tokens from Any Analysis
However, with all that said, stopwords CAN be useful in some situations. I combine stopwords with the shingle factory to create "interesting phrases" (not really) that i use in "my more like this" needs. for example, europe for vacation europe on vacation will create the shingle europe_vacation which i can then use to relate other documents that would be much more similar in such regard, rather than just using the "interesting words" europe, vacation with stop words, the shingles would be europe_for for_vacation and europe_on on_vacation just something to keep in mind, theres a lot of creative ways to use stopwords depending on your needs. i use the above for a VERY basic ML teacher and it works way better than using stopwords, On Wed, Oct 9, 2019 at 10:51 AM Erick Erickson wrote: > The theory behind stopwords is that they are “safe” to remove when > calculating relevance, so we can squeeze every last bit of usefulness out > of very constrained hardware (think 64K of memory. Yes kilobytes). We’ve > come a long way since then and the necessity of removing stopwords from the > indexed tokens to conserve RAM and disk is much less relevant than it used > to be in “the bad old days” when the idea of stopwords was invented. > > I’m not quite so confident as Alex that there is “no benefit”, but I’ll > totally agree that you should remove stopwords only _after_ you have some > evidence that removing them is A Good Thing in your situation. > > And removing stopwords leads to some interesting corner cases. Consider a > search for “to be or not to be” if they’re all stopwords. > > Best, > Erick > > > On Oct 9, 2019, at 9:38 AM, Audrey Lorberfeld - > audrey.lorberf...@ibm.com wrote: > > > > Hey Alex, > > > > Thank you! > > > > Re: stopwords being a thing of the past due to the affordability of > hardware...can you expand? I'm not sure I understand. > > > > -- > > Audrey Lorberfeld > > Data Scientist, w3 Search > > IBM > > audrey.lorberf...@ibm.com > > > > > > On 10/8/19, 1:01 PM, "David Hastings" > wrote: > > > >Another thing to add to the above, > >> > >> IT:ibm. In this case, we would want to maintain the colon and the > >> capitalization (otherwise “it” would be taken out as a stopword). > >> > >stopwords are a thing of the past at this point. there is no benefit > to > >using them now with hardware being so cheap. > > > >On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch < > arafa...@gmail.com> > >wrote: > > > >> If you don't want it to be touched by a tokenizer, how would the > >> protection step know that the sequence of characters you want to > >> protect is "IT:ibm" and not "this is an IT:ibm term I want to > >> protect"? > >> > >> What it sounds to me is that you may want to: > >> 1) copyField to a second field > >> 2) Apply a much lighter (whitespace?) tokenizer to that second field > >> 3) Run the results through something like KeepWordFilterFactory > >> 4) Search both fields with a boost on the second, higher-signal field > >> > >> The other option is to run CharacterFilter, > >> (PatternReplaceCharFilterFactory) which is pre-tokenizer to map known > >> complex acronyms to non-tokenizable substitutions. E.g. "IT:ibm -> > >> term365". As long as it is done on both indexing and query, they will > >> still match. You may have to have a bunch of them or write some sort > >> of lookup map. > >> > >> Regards, > >> Alex. > >> > >> On Tue, 8 Oct 2019 at 12:10, Audrey Lorberfeld - > >> audrey.lorberf...@ibm.com wrote: > >>> > >>> Hi All, > >>> > >>> This is likely a rudimentary question, but I can’t seem to find a > >> straight-forward answer on forums or the documentation…is there a way to > >> protect tokens from ANY analysis? I know things like the > >> KeywordMarkerFilterFactory protect tokens from stemming, but we have > some > >> terms we don’t even want our tokenizer to touch. Mostly, these are > >> IBM-specific acronyms, such as IT:ibm. In this case, we would want to > >> maintain the colon and the capitalization (otherwise “it” would be taken > >> out as a stopword). > >>> > >>> Any advice is appreciated! > >>> > >>> Thank you, > >>> Audrey > >>> > >>> -- > >>> Audrey Lorberfeld > >>> Data Scientist, w3 Search > >>> IBM > >>> audrey.lorberf...@ibm.com > >>> > >> > > > > > >
Re: Re: Protecting Tokens from Any Analysis
another add on, as the previous two were pretty much spot on: https://www.google.com/search?rlz=1C5CHFA_enUS814US819=ACYBGNTi2tQTQH6TycDKwRNEn9g2km9awg%3A1570632176627=8PGdXa7tJeem_QaatJ_oAg=drive+in=drive+in_l=psy-ab.3..0l10.35669.36730..37042...0.4..1.434.1152.4j3j4-1..01..gws-wiz...0i71j35i39j0i273j0i67j0i131j0i273i70i249.agjl1cqAyog=0ahUKEwiupdfntI_lAhVnU98KHRraBy0Q4dUDCAs=5 vs https://www.google.com/search?rlz=1C5CHFA_enUS814US819=ACYBGNRFNjzWADDR7awohPfgg8qGXqOlmg%3A1570632182338=9vGdXZ2VFKW8ggeuw73IDQ=drive+on=drive+on_l=psy-ab.3..0l10.35301.37396..37917...0.4..0.83.590.82..01..gws-wiz...0i71j35i39j0i273j0i131j0i67j0i3.34FIDQtvfOE=0ahUKEwid6LPqtI_lAhUlnuAKHa5hD9kQ4dUDCAs=5 On Wed, Oct 9, 2019 at 10:41 AM Alexandre Rafalovitch wrote: > Stopwords (it was discussed on mailing list several times I recall): > The ideas is that it used to be part of the tricks to make the index > as small as possible to allow faster search. Stopwords being the most > common words > This days, disk space is not an issue most of the time and there have > been many optimizations to make stopwords less relevant. Plus, like > you said, sometimes the stopword management actively gets in the way. > Here is an interesting - if old - article about it too: > > https://library.stanford.edu/blogs/digital-library-blog/2011/12/stopwords-searchworks-be-or-not-be > > Regards, >Alex. > > On Wed, 9 Oct 2019 at 09:39, Audrey Lorberfeld - > audrey.lorberf...@ibm.com wrote: > > > > Hey Alex, > > > > Thank you! > > > > Re: stopwords being a thing of the past due to the affordability of > hardware...can you expand? I'm not sure I understand. > > > > -- > > Audrey Lorberfeld > > Data Scientist, w3 Search > > IBM > > audrey.lorberf...@ibm.com > > > > > > On 10/8/19, 1:01 PM, "David Hastings" > wrote: > > > > Another thing to add to the above, > > > > > > IT:ibm. In this case, we would want to maintain the colon and the > > > capitalization (otherwise “it” would be taken out as a stopword). > > > > > stopwords are a thing of the past at this point. there is no > benefit to > > using them now with hardware being so cheap. > > > > On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch < > arafa...@gmail.com> > > wrote: > > > > > If you don't want it to be touched by a tokenizer, how would the > > > protection step know that the sequence of characters you want to > > > protect is "IT:ibm" and not "this is an IT:ibm term I want to > > > protect"? > > > > > > What it sounds to me is that you may want to: > > > 1) copyField to a second field > > > 2) Apply a much lighter (whitespace?) tokenizer to that second > field > > > 3) Run the results through something like KeepWordFilterFactory > > > 4) Search both fields with a boost on the second, higher-signal > field > > > > > > The other option is to run CharacterFilter, > > > (PatternReplaceCharFilterFactory) which is pre-tokenizer to map > known > > > complex acronyms to non-tokenizable substitutions. E.g. "IT:ibm -> > > > term365". As long as it is done on both indexing and query, they > will > > > still match. You may have to have a bunch of them or write some > sort > > > of lookup map. > > > > > > Regards, > > >Alex. > > > > > > On Tue, 8 Oct 2019 at 12:10, Audrey Lorberfeld - > > > audrey.lorberf...@ibm.com wrote: > > > > > > > > Hi All, > > > > > > > > This is likely a rudimentary question, but I can’t seem to find a > > > straight-forward answer on forums or the documentation…is there a > way to > > > protect tokens from ANY analysis? I know things like the > > > KeywordMarkerFilterFactory protect tokens from stemming, but we > have some > > > terms we don’t even want our tokenizer to touch. Mostly, these are > > > IBM-specific acronyms, such as IT:ibm. In this case, we would want > to > > > maintain the colon and the capitalization (otherwise “it” would be > taken > > > out as a stopword). > > > > > > > > Any advice is appreciated! > > > > > > > > Thank you, > > > > Audrey > > > > > > > > -- > > > > Audrey Lorberfeld > > > > Data Scientist, w3 Search > > > > IBM > > > > audrey.lorberf...@ibm.com > > > > > > > > > > > >
Re: Re: Protecting Tokens from Any Analysis
The theory behind stopwords is that they are “safe” to remove when calculating relevance, so we can squeeze every last bit of usefulness out of very constrained hardware (think 64K of memory. Yes kilobytes). We’ve come a long way since then and the necessity of removing stopwords from the indexed tokens to conserve RAM and disk is much less relevant than it used to be in “the bad old days” when the idea of stopwords was invented. I’m not quite so confident as Alex that there is “no benefit”, but I’ll totally agree that you should remove stopwords only _after_ you have some evidence that removing them is A Good Thing in your situation. And removing stopwords leads to some interesting corner cases. Consider a search for “to be or not to be” if they’re all stopwords. Best, Erick > On Oct 9, 2019, at 9:38 AM, Audrey Lorberfeld - audrey.lorberf...@ibm.com > wrote: > > Hey Alex, > > Thank you! > > Re: stopwords being a thing of the past due to the affordability of > hardware...can you expand? I'm not sure I understand. > > -- > Audrey Lorberfeld > Data Scientist, w3 Search > IBM > audrey.lorberf...@ibm.com > > > On 10/8/19, 1:01 PM, "David Hastings" wrote: > >Another thing to add to the above, >> >> IT:ibm. In this case, we would want to maintain the colon and the >> capitalization (otherwise “it” would be taken out as a stopword). >> >stopwords are a thing of the past at this point. there is no benefit to >using them now with hardware being so cheap. > >On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch >wrote: > >> If you don't want it to be touched by a tokenizer, how would the >> protection step know that the sequence of characters you want to >> protect is "IT:ibm" and not "this is an IT:ibm term I want to >> protect"? >> >> What it sounds to me is that you may want to: >> 1) copyField to a second field >> 2) Apply a much lighter (whitespace?) tokenizer to that second field >> 3) Run the results through something like KeepWordFilterFactory >> 4) Search both fields with a boost on the second, higher-signal field >> >> The other option is to run CharacterFilter, >> (PatternReplaceCharFilterFactory) which is pre-tokenizer to map known >> complex acronyms to non-tokenizable substitutions. E.g. "IT:ibm -> >> term365". As long as it is done on both indexing and query, they will >> still match. You may have to have a bunch of them or write some sort >> of lookup map. >> >> Regards, >> Alex. >> >> On Tue, 8 Oct 2019 at 12:10, Audrey Lorberfeld - >> audrey.lorberf...@ibm.com wrote: >>> >>> Hi All, >>> >>> This is likely a rudimentary question, but I can’t seem to find a >> straight-forward answer on forums or the documentation…is there a way to >> protect tokens from ANY analysis? I know things like the >> KeywordMarkerFilterFactory protect tokens from stemming, but we have some >> terms we don’t even want our tokenizer to touch. Mostly, these are >> IBM-specific acronyms, such as IT:ibm. In this case, we would want to >> maintain the colon and the capitalization (otherwise “it” would be taken >> out as a stopword). >>> >>> Any advice is appreciated! >>> >>> Thank you, >>> Audrey >>> >>> -- >>> Audrey Lorberfeld >>> Data Scientist, w3 Search >>> IBM >>> audrey.lorberf...@ibm.com >>> >> > >
Re: Re: Protecting Tokens from Any Analysis
Stopwords (it was discussed on mailing list several times I recall): The ideas is that it used to be part of the tricks to make the index as small as possible to allow faster search. Stopwords being the most common words This days, disk space is not an issue most of the time and there have been many optimizations to make stopwords less relevant. Plus, like you said, sometimes the stopword management actively gets in the way. Here is an interesting - if old - article about it too: https://library.stanford.edu/blogs/digital-library-blog/2011/12/stopwords-searchworks-be-or-not-be Regards, Alex. On Wed, 9 Oct 2019 at 09:39, Audrey Lorberfeld - audrey.lorberf...@ibm.com wrote: > > Hey Alex, > > Thank you! > > Re: stopwords being a thing of the past due to the affordability of > hardware...can you expand? I'm not sure I understand. > > -- > Audrey Lorberfeld > Data Scientist, w3 Search > IBM > audrey.lorberf...@ibm.com > > > On 10/8/19, 1:01 PM, "David Hastings" wrote: > > Another thing to add to the above, > > > > IT:ibm. In this case, we would want to maintain the colon and the > > capitalization (otherwise “it” would be taken out as a stopword). > > > stopwords are a thing of the past at this point. there is no benefit to > using them now with hardware being so cheap. > > On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch > wrote: > > > If you don't want it to be touched by a tokenizer, how would the > > protection step know that the sequence of characters you want to > > protect is "IT:ibm" and not "this is an IT:ibm term I want to > > protect"? > > > > What it sounds to me is that you may want to: > > 1) copyField to a second field > > 2) Apply a much lighter (whitespace?) tokenizer to that second field > > 3) Run the results through something like KeepWordFilterFactory > > 4) Search both fields with a boost on the second, higher-signal field > > > > The other option is to run CharacterFilter, > > (PatternReplaceCharFilterFactory) which is pre-tokenizer to map known > > complex acronyms to non-tokenizable substitutions. E.g. "IT:ibm -> > > term365". As long as it is done on both indexing and query, they will > > still match. You may have to have a bunch of them or write some sort > > of lookup map. > > > > Regards, > >Alex. > > > > On Tue, 8 Oct 2019 at 12:10, Audrey Lorberfeld - > > audrey.lorberf...@ibm.com wrote: > > > > > > Hi All, > > > > > > This is likely a rudimentary question, but I can’t seem to find a > > straight-forward answer on forums or the documentation…is there a way to > > protect tokens from ANY analysis? I know things like the > > KeywordMarkerFilterFactory protect tokens from stemming, but we have > some > > terms we don’t even want our tokenizer to touch. Mostly, these are > > IBM-specific acronyms, such as IT:ibm. In this case, we would want to > > maintain the colon and the capitalization (otherwise “it” would be taken > > out as a stopword). > > > > > > Any advice is appreciated! > > > > > > Thank you, > > > Audrey > > > > > > -- > > > Audrey Lorberfeld > > > Data Scientist, w3 Search > > > IBM > > > audrey.lorberf...@ibm.com > > > > > > >
Re: Re: Protecting Tokens from Any Analysis
Stopwords were used when we were running search engines on 16-bit computers with 50 Megabyte disks, like the PDP-11. They avoided storing and processing long posting lists. Think of removing stopwords as a binary weighting on frequent terms, either on or off (not in the index). With idf, we have a proportional weighting for frequent terms. That gives better results than binary weighting. Removing stopwords makes some searches impossible. The classic example is “to be or not to be”, which is 100% stopwords. This is a real-world problem. When I was building search for Netflix a dozen years ago, I hit several movie or TV titles which were all stopwords. I wrote about them in this blog post. https://observer.wunderwood.org/2007/05/31/do-all-stopword-queries-matter/ wunder Walter Underwood wun...@wunderwood.org http://observer.wunderwood.org/ (my blog) > On Oct 9, 2019, at 6:38 AM, Audrey Lorberfeld - audrey.lorberf...@ibm.com > wrote: > > Hey Alex, > > Thank you! > > Re: stopwords being a thing of the past due to the affordability of > hardware...can you expand? I'm not sure I understand. > > -- > Audrey Lorberfeld > Data Scientist, w3 Search > IBM > audrey.lorberf...@ibm.com > > > On 10/8/19, 1:01 PM, "David Hastings" wrote: > >Another thing to add to the above, >> >> IT:ibm. In this case, we would want to maintain the colon and the >> capitalization (otherwise “it” would be taken out as a stopword). >> >stopwords are a thing of the past at this point. there is no benefit to >using them now with hardware being so cheap. > >On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch >wrote: > >> If you don't want it to be touched by a tokenizer, how would the >> protection step know that the sequence of characters you want to >> protect is "IT:ibm" and not "this is an IT:ibm term I want to >> protect"? >> >> What it sounds to me is that you may want to: >> 1) copyField to a second field >> 2) Apply a much lighter (whitespace?) tokenizer to that second field >> 3) Run the results through something like KeepWordFilterFactory >> 4) Search both fields with a boost on the second, higher-signal field >> >> The other option is to run CharacterFilter, >> (PatternReplaceCharFilterFactory) which is pre-tokenizer to map known >> complex acronyms to non-tokenizable substitutions. E.g. "IT:ibm -> >> term365". As long as it is done on both indexing and query, they will >> still match. You may have to have a bunch of them or write some sort >> of lookup map. >> >> Regards, >> Alex. >> >> On Tue, 8 Oct 2019 at 12:10, Audrey Lorberfeld - >> audrey.lorberf...@ibm.com wrote: >>> >>> Hi All, >>> >>> This is likely a rudimentary question, but I can’t seem to find a >> straight-forward answer on forums or the documentation…is there a way to >> protect tokens from ANY analysis? I know things like the >> KeywordMarkerFilterFactory protect tokens from stemming, but we have some >> terms we don’t even want our tokenizer to touch. Mostly, these are >> IBM-specific acronyms, such as IT:ibm. In this case, we would want to >> maintain the colon and the capitalization (otherwise “it” would be taken >> out as a stopword). >>> >>> Any advice is appreciated! >>> >>> Thank you, >>> Audrey >>> >>> -- >>> Audrey Lorberfeld >>> Data Scientist, w3 Search >>> IBM >>> audrey.lorberf...@ibm.com >>> >> > >
Re: Re: Protecting Tokens from Any Analysis
Hey Alex, Thank you! Re: stopwords being a thing of the past due to the affordability of hardware...can you expand? I'm not sure I understand. -- Audrey Lorberfeld Data Scientist, w3 Search IBM audrey.lorberf...@ibm.com On 10/8/19, 1:01 PM, "David Hastings" wrote: Another thing to add to the above, > > IT:ibm. In this case, we would want to maintain the colon and the > capitalization (otherwise “it” would be taken out as a stopword). > stopwords are a thing of the past at this point. there is no benefit to using them now with hardware being so cheap. On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch wrote: > If you don't want it to be touched by a tokenizer, how would the > protection step know that the sequence of characters you want to > protect is "IT:ibm" and not "this is an IT:ibm term I want to > protect"? > > What it sounds to me is that you may want to: > 1) copyField to a second field > 2) Apply a much lighter (whitespace?) tokenizer to that second field > 3) Run the results through something like KeepWordFilterFactory > 4) Search both fields with a boost on the second, higher-signal field > > The other option is to run CharacterFilter, > (PatternReplaceCharFilterFactory) which is pre-tokenizer to map known > complex acronyms to non-tokenizable substitutions. E.g. "IT:ibm -> > term365". As long as it is done on both indexing and query, they will > still match. You may have to have a bunch of them or write some sort > of lookup map. > > Regards, >Alex. > > On Tue, 8 Oct 2019 at 12:10, Audrey Lorberfeld - > audrey.lorberf...@ibm.com wrote: > > > > Hi All, > > > > This is likely a rudimentary question, but I can’t seem to find a > straight-forward answer on forums or the documentation…is there a way to > protect tokens from ANY analysis? I know things like the > KeywordMarkerFilterFactory protect tokens from stemming, but we have some > terms we don’t even want our tokenizer to touch. Mostly, these are > IBM-specific acronyms, such as IT:ibm. In this case, we would want to > maintain the colon and the capitalization (otherwise “it” would be taken > out as a stopword). > > > > Any advice is appreciated! > > > > Thank you, > > Audrey > > > > -- > > Audrey Lorberfeld > > Data Scientist, w3 Search > > IBM > > audrey.lorberf...@ibm.com > > >
Re: Protecting Tokens from Any Analysis
Another thing to add to the above, > > IT:ibm. In this case, we would want to maintain the colon and the > capitalization (otherwise “it” would be taken out as a stopword). > stopwords are a thing of the past at this point. there is no benefit to using them now with hardware being so cheap. On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch wrote: > If you don't want it to be touched by a tokenizer, how would the > protection step know that the sequence of characters you want to > protect is "IT:ibm" and not "this is an IT:ibm term I want to > protect"? > > What it sounds to me is that you may want to: > 1) copyField to a second field > 2) Apply a much lighter (whitespace?) tokenizer to that second field > 3) Run the results through something like KeepWordFilterFactory > 4) Search both fields with a boost on the second, higher-signal field > > The other option is to run CharacterFilter, > (PatternReplaceCharFilterFactory) which is pre-tokenizer to map known > complex acronyms to non-tokenizable substitutions. E.g. "IT:ibm -> > term365". As long as it is done on both indexing and query, they will > still match. You may have to have a bunch of them or write some sort > of lookup map. > > Regards, >Alex. > > On Tue, 8 Oct 2019 at 12:10, Audrey Lorberfeld - > audrey.lorberf...@ibm.com wrote: > > > > Hi All, > > > > This is likely a rudimentary question, but I can’t seem to find a > straight-forward answer on forums or the documentation…is there a way to > protect tokens from ANY analysis? I know things like the > KeywordMarkerFilterFactory protect tokens from stemming, but we have some > terms we don’t even want our tokenizer to touch. Mostly, these are > IBM-specific acronyms, such as IT:ibm. In this case, we would want to > maintain the colon and the capitalization (otherwise “it” would be taken > out as a stopword). > > > > Any advice is appreciated! > > > > Thank you, > > Audrey > > > > -- > > Audrey Lorberfeld > > Data Scientist, w3 Search > > IBM > > audrey.lorberf...@ibm.com > > >
Re: Protecting Tokens from Any Analysis
If you don't want it to be touched by a tokenizer, how would the protection step know that the sequence of characters you want to protect is "IT:ibm" and not "this is an IT:ibm term I want to protect"? What it sounds to me is that you may want to: 1) copyField to a second field 2) Apply a much lighter (whitespace?) tokenizer to that second field 3) Run the results through something like KeepWordFilterFactory 4) Search both fields with a boost on the second, higher-signal field The other option is to run CharacterFilter, (PatternReplaceCharFilterFactory) which is pre-tokenizer to map known complex acronyms to non-tokenizable substitutions. E.g. "IT:ibm -> term365". As long as it is done on both indexing and query, they will still match. You may have to have a bunch of them or write some sort of lookup map. Regards, Alex. On Tue, 8 Oct 2019 at 12:10, Audrey Lorberfeld - audrey.lorberf...@ibm.com wrote: > > Hi All, > > This is likely a rudimentary question, but I can’t seem to find a > straight-forward answer on forums or the documentation…is there a way to > protect tokens from ANY analysis? I know things like the > KeywordMarkerFilterFactory protect tokens from stemming, but we have some > terms we don’t even want our tokenizer to touch. Mostly, these are > IBM-specific acronyms, such as IT:ibm. In this case, we would want to > maintain the colon and the capitalization (otherwise “it” would be taken out > as a stopword). > > Any advice is appreciated! > > Thank you, > Audrey > > -- > Audrey Lorberfeld > Data Scientist, w3 Search > IBM > audrey.lorberf...@ibm.com >
