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From "Michael Busch (JIRA)" <>
Subject [jira] Commented: (LUCENE-965) Implement a state-of-the-art retrieval function in Lucene
Date Thu, 26 Jul 2007 19:38:03 GMT


Michael Busch commented on LUCENE-965:

> Can we store the "document length" (with multiple fields) and "average document length"

> as the payload data at document level and index level respectively? The current payload

> is designed at term level, is it right? If we want to store something at document and

> index level, do we necessary change the Lucene file format? 

You are right, currently we can only store payloads per term occurrence, not at the doc
level. However, it is possible to simply add a special term to every document that has
only one occurrence with a payload, then you have one payload per doc.

Coincidentally I am currently testing how search performance would suffer if we stored
the norms as payloads in the posting lists. At search time we would then not buffer the
norms but read them on demand from the prx file. This is probably somewhat slower than 
buffering the norms, but has a lot of advantages, such as much simpler code and less 
memory consumption by the IndexReader. Since all norms are then stored in a single 
posting lists I'm hoping that the FS cache will help that the search performance won't
suffer too much. And multi-level skipping should help too. Well let's see, I'm currently
building an index with norms as payloads, I should have some numbers tonight or tomorrow.

> Implement a state-of-the-art retrieval function in Lucene
> ---------------------------------------------------------
>                 Key: LUCENE-965
>                 URL:
>             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

> 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
 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, 
> the query is "+w3 xx", and we have two documents "w1 xx w2 yy w3" and "w1 w3 xx w2 yy
> 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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