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https://issues.apache.org/jira/browse/LUCENE-965?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#action_12515846
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Grant Ingersoll commented on LUCENE-965:
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I guess I would not be in favor of a special term, I would rather see it
integrated into the file format somehow. Special terms get deleted, misused,
etc. Plus the avg. doc length is going to be something that is going to need
to be updated frequently, right?
Since we are talking 3.x of Lucene fairly soon anyway (assuming the JDK 1.5
vote passes), this would allow us to make the file format change as well, as
long as we can still read prior versions.
Charlie, as for you question about what users value in Lucene, speed or recall
and precision, the answer is both. :-) Some people care more about speed
while others care about p/r. I think most people that use Lucene have the
feeling that the results are good enough in production environments and that we
don't always worry about getting every last bit out of TREC (especially since
we can't, as a group, test against TREC). That being said, I would bet most
users would be willing to trade off a few percentage points of speed in
exchange for the kind of MAP improvements we are talking here. Especially
since we probably can eventually figure out a way to make it as fast anyway, or
at least find other things we can speed up.
Correct me if I am wrong, but there are other IR strategies that can use the
avg. doc. length, too, right? So, not to sidetrack too much, but if we do this
right, maybe we can also open up the door to other scoring strategies as well
without much downside. Just something to consider.
> Implement a state-of-the-art retrieval function in Lucene
> ---------------------------------------------------------
>
> Key: LUCENE-965
> URL: https://issues.apache.org/jira/browse/LUCENE-965
> Project: Lucene - Java
> Issue Type: Improvement
> Components: Search
> Affects Versions: 2.2
> Reporter: Hui Fang
> Attachments: axiomaticFunction.patch
>
>
> We implemented the axiomatic retrieval function, which is a state-of-the-art
> retrieval function, to
> replace the default similarity function in Lucene. We compared the
> performance of these two functions and reported the results at
> http://sifaka.cs.uiuc.edu/hfang/lucene/Lucene_exp.pdf.
> The report shows that the performance of the axiomatic retrieval function is
> much better than the default function. The axiomatic retrieval function is
> able to find more relevant documents and users can see more relevant
> documents in the top-ranked documents. Incorporating such a state-of-the-art
> retrieval function could improve the search performance of all the
> applications which were built upon Lucene.
> Most changes related to the implementation are made in AXSimilarity,
> TermScorer and TermQuery.java. However, many test cases are hand coded to
> test whether the implementation of the default function is correct. Thus, I
> also made the modification to many test files to make the new retrieval
> function pass those cases. In fact, we found that some old test cases are not
> reasonable. For example, in the testQueries02 of TestBoolean2.java,
> the query is "+w3 xx", and we have two documents "w1 xx w2 yy w3" and "w1 w3
> xx w2 yy w3".
> The second document should be more relevant than the first one, because it
> has more
> occurrences of the query term "w3". But the original test case would require
> us to rank
> the first document higher than the second one, which is not reasonable.
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