This relies on the circulation and rating data still being tied to the patron in the system, though - yes, it'd be on the database side and not on public view, but it's still creating a picture of a patron's reading history that has privacy implications. Of course, this feature should be set for systems to enable or disable, so that systems that are concerned about privacy simply won't turn it on. (PINES, for example, limits the retention of circulation history in the system as much as we can because of our privacy policies, so any feature that is linked to a patron's history would be unusable for us.)
If ranking data were stored completely independently of the patron, then library systems would be able to use it without privacy concerns, and patrons wouldn't even need to be logged in to use it - but then it wouldn't be able to give completely customized recommendations to a specific patron, either. It's a definite tradeoff. Terran McCanna PINES Program Manager Georgia Public Library Service 1800 Century Place, Suite 150 Atlanta, GA 30345 404-235-7138 [email protected] ----- Original Message ----- From: "Vanya Jauhal" <[email protected]> To: "Evergreen Discussion Group" <[email protected]> Sent: Thursday, September 25, 2014 3:41:02 PM Subject: Re: [OPEN-ILS-GENERAL] Awesome Box Integration Hello Rogan This is exactly what I had in mind. All the recommendation processing will take place in background, and all the user will see is a recommendation and not the information of any other patron. This way his experience with Awesome Box will get enhanced. And yes, we can maybe, start off with some broad level genres, like, as you mentioned, fiction, non-fiction, documentaries, etc. Then, depending upon the infrastructure of the system and the response of that categorization, we can build upon the algorithm accordingly. You are right- it would be a big task in itself, but since the number of parameters involved are few and explicit, it gets simplified to an extent. On Fri, Sep 26, 2014 at 12:50 AM, Rogan Hamby < [email protected] > wrote: I don't see an issue with doing analysis of circulation patterns on the backend so long as nothing identifying is exposed. For example, if all I saw as a patron was a tab in my opac that said "you thought The Yiddish Policeman's Union was Awesome! Some others do did also thought this was Awesome .... " I don't see that as different from doing the same thing with circulations. It's not telling patrons even what the points of comparison were unless they only had a single item in their circulation history and even then it doesn't tell them how many other patrons, how much, etc.... I'm dubious about subject headings also but wouldn't want to dismiss it out of hand. It might work. Without doing some experimenting I could see it going either way. Some fixed fields I could see working, like fiction and non-fiction. Age groups? Well, at least I can tell you I can't rely on those in my catalog. :) However, I also worry that reading recommendations based on circulation history could easily grow into a much more complicated task, especially depending on how we deliver those recommendations. Looking at a single boolean value tied to the user and item (circ table?) could still be quite a project by itself especially once all the useful bits and pieces are built in. On Thu, Sep 25, 2014 at 2:37 PM, McCanna, Terran < [email protected] > wrote: Agreed - it's a great idea in theory, but I'm not sure how well it would work in actual practice. Even in a single library, genre subject headings are usually pretty inconsistent in the MARC records because of copy cataloging, and that usually gets even more inconsistent in a consortium of libraries. Perhaps it could be partially weighted on genre subject headings, but not overly reliant on them? It might be worth considering the fixed field values for fiction vs. non-fiction and for age groups, too. I love the idea of providing recommendations based on other people that have similar taste ("other people that liked this book also liked these books...") but if the data is tied to actual patrons (and I'm not sure how it couldn't be) then quite a few library systems would face legal privacy issues and wouldn't be able to use it. We're currently using a commercial service to pull in reading recommendations because the recommendations can't be tied back to any of our patrons. Terran McCanna PINES Program Manager Georgia Public Library Service 1800 Century Place, Suite 150 Atlanta, GA 30345 404-235-7138 [email protected] ----- Original Message ----- From: "Rogan Hamby" < [email protected] > To: "Evergreen Discussion Group" < [email protected] > Sent: Thursday, September 25, 2014 2:02:58 PM Subject: Re: [OPEN-ILS-GENERAL] Awesome Box Integration I can see some challenges to tracking genre and I'd be hesitant to put too much value on it. There are ways to catalog it but in my experience actually relying on it being in records (much less being consistent) is very unreliable in organizations that do a lot of copy cataloging / don't have centralized and controlled cataloging and there quite a few in that boat. That concern aside, I've always thought this would be a fun and potentially valuable thing to add. On Thu, Sep 25, 2014 at 1:44 PM, Vanya Jauhal < [email protected] > wrote: Hello everyone I'm Vanya, from India. I'm a candidate for OPW Round9 internship with evergreen. While discussing the idea of Awesome Box integration with Evergreen, Kathy and I discussed the possibility of making the Evergreen support for Awesome Box more interpretive using Artificial Intelligence. What if we could train the system to give weightage to people's "awesome" tags on items, depending upon how much their previous tags are appreciated by other people. For example: Let's say you tag a book to be awesome. Now, if 100 other people check that book in, and (lets say) 80 of them also tag it to be awesome- it will mean that your opinion matches a majority of people. On the other hand, if 100 other people check that book in and (say) only 5 of them tag it as awesome, this would mean that your awesome tag is not in coherence with the majority. So, in the former case, your awesome tag can be given more weightage as compared to the latter. Also, the weightage may vary according to genres. So- you may have a good taste in mystery books but your taste in classical literature might not be the same as the majority crowd. So- the weightage of your awesome tag in mystery would be higher than classical literature. We can even extend it to provide recommendations to users depending on their coherence with other users with similar taste. I am looking forward to your suggestions and feedback on this. Thank you for your time Vanya -- Rogan Hamby, MLS, CCNP, MIA Managers Headquarters Library and Reference Services, York County Library System “You can never get a cup of tea large enough or a book long enough to suit me.” ― C.S. Lewis -- Rogan Hamby, MLS, CCNP, MIA Managers Headquarters Library and Reference Services, York County Library System “You can never get a cup of tea large enough or a book long enough to suit me.” ― C.S. Lewis
