This sounds good to me, as it would lead us to pluggable similarity
computation...mmmm.
I can refactor some of this tonight.
Otis
--- Doug Cutting <[EMAIL PROTECTED]> wrote:
> This looks like a good approach. When I get a chance, I'd like to
> make
> Similarity an interface or an abstract class, whose default
> implementation would do what the current class does, but whose
> methods
> can be overridden. Then I'd add methods like:
>
> public static void Similarity.setDefaultSimilarity(Similarity
> sim);
> public void IndexWriter.setSimilarity(Similarity sim);
> public void Searcher.setSimilarity(Similarity sim);
>
> So to override Similarity methods you'd define a subclass of the
> standard implementation, then either install yours globally via
> setDefaultSimilarity, or set it in your IndexWriter before adding
> documents and in your Searcher before searching. Does that sound
> reasonable?
>
> This would let you do what you describe below without changing
> Lucene's
> sources. However I'm very short on time right now and don't know how
>
> soon I'll get to this.
>
> Doug
>
> David Birtwell wrote:
> > Hi Dmitry,
> >
> > I was faced with a similar problem. We wanted to have a numeric
> rank
> > field in each document influence the order in which the documents
> were
> > returned by lucene. While investigating a solution for this, I
> wanted
> > to see if I could implement strict sorting based on this numeric
> value.
> > I was able to accomplish this using document boosting, but not
> without
> > modifying the lucene source. Our "ranking" field is an integer
> value
> > from one to one hundred. I'm not sure if this will help you, but
> I'll
> > include a summary of what I did.
> >
> > In DocumentWriter remove the normalization by field length:
> > float norm = fieldBoosts[n] *
> > Similarity.normalizeLength(fieldLengths[n]);
> > to
> > float norm = fieldBoosts[n];
> >
> > In TermScorer and PhraseScorer, modify the score() method to ignore
> the
> > lucene base score:
> > score *= Similarity.decodeNorm(norms[d]);
> > to
> > score = Similarity.decodeNorm(norms[d]);
> >
> > In Similarity.java, make byteToFloat() public.
> >
> > At index time, use Similarity.byteToFloat() to determine your boost
>
> > value as in the following pseudocode:
> > Document d = new Document();
> > ... add your fields ...
> > int rank = d.getField("RANK"); (range of rank can be 0 to 255)
> > float sortVal = Similarity.byteToFloat(rank)
> > d.setBoost(sortVal)
> >
> > If you'd like the reasoning behind any or all of these items, let
> me know.
> >
> > DaveB
> >
> >
> >
> > Dmitry Serebrennikov wrote:
> >
> >> Greetings Everyone,
> >>
> >> I'm thinking of trying to build something that manipulates a query
>
> >> score in order to achieve a sort order other then the default
> >> relevance sort. The idea is to create a new type of query:
> >> SortingQuery( Query query, String sortByField )
> >>
> >> It would run the sub-query and return results in an order of the
> >> values found in the "sortByField" for those documents. Now, I've
> >> looked at all of the sorting discussion prior to this, and the
> best
> >> approach (recommended by Doug among others) is to provide some
> sort of
> >> a fast access to the field values inside the HitCollector. Reading
>
> >> documents at search time is too slow, so people access the data
> >> elsewhere or build an in-memory index of that data (such as is
> done in
> >> the SearchBean's SortField).
> >>
> >> My idea is different. I want to try to do the following:
> >> - compose a query that consists of the original sub-query followed
> by
> >> a special "sorting query"
> >> - "boost" the score of the original sub-query to 0
> >> - compute the score of the sorting query such that it would
> reflect
> >> the desired sort order
> >>
> >> Has anyone tried to do something like this?
> >> Would this work?
> >> Is this worth doing?
> >> If it would, would then I have to do something during the indexing
>
> >> time to set normalization / scoring factors for that field to
> >> something or other?
> >>
> >> Thanks.
> >> Dmitry.
> >>
> >>
> >>
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> >>
> >>
> >
> >
> >
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>
>
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