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Posted to dev@lucene.apache.org by "Mayya Sharipova (JIRA)" <ji...@apache.org> on 2019/03/05 00:11:00 UTC
[jira] [Commented] (LUCENE-6968) LSH Filter
[ https://issues.apache.org/jira/browse/LUCENE-6968?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16783921#comment-16783921 ]
Mayya Sharipova commented on LUCENE-6968:
-----------------------------------------
[~andyhind] Thanks very much for your answer, it made things more clear. I still have a couple of additional questions if you don't mind:
1) The default settings of the filter will produce for each document 512 tokens each of the size 16 bytes, that is approximately 8Kb. Isn't 8Kb too big of a size to be a document's signature?
2) What is the way to combine `min_hash` tokens to a query for similarity search? Do you have any examples? Is this a work in progress?
Thanks again!
> LSH Filter
> ----------
>
> Key: LUCENE-6968
> URL: https://issues.apache.org/jira/browse/LUCENE-6968
> Project: Lucene - Core
> Issue Type: Improvement
> Components: modules/analysis
> Reporter: Cao Manh Dat
> Assignee: Tommaso Teofili
> Priority: Major
> Fix For: 6.2, 7.0
>
> Attachments: LUCENE-6968.4.patch, LUCENE-6968.5.patch, LUCENE-6968.6.patch, LUCENE-6968.patch, LUCENE-6968.patch, LUCENE-6968.patch
>
>
> I'm planning to implement LSH. Which support query like this
> {quote}
> Find similar documents that have 0.8 or higher similar score with a given document. Similarity measurement can be cosine, jaccard, euclid..
> {quote}
> For example. Given following corpus
> {quote}
> 1. Solr is an open source search engine based on Lucene
> 2. Solr is an open source enterprise search engine based on Lucene
> 3. Solr is an popular open source enterprise search engine based on Lucene
> 4. Apache Lucene is a high-performance, full-featured text search engine library written entirely in Java
> {quote}
> We wanna find documents that have 0.6 score in jaccard measurement with this doc
> {quote}
> Solr is an open source search engine
> {quote}
> It will return only docs 1,2 and 3 (MoreLikeThis will also return doc 4)
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