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https://issues.apache.org/jira/browse/LUCENE-6968?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15263867#comment-15263867
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Andy Hind commented on LUCENE-6968:
-----------------------------------
After a bit more digging, the single hash and keeping the minimum set can be
improved.
See:
[1] http://jmlr.org/proceedings/papers/v32/shrivastava14.pdf
[2] http://www.auai.org/uai2014/proceedings/individuals/225.pdf
In summary: rather than keep the minimum set, split the hash space up into 500
buckets (for a 500 hash fingerprint) and keep the minimum for each bucket. To
fill an empty bucket, take the minimum from the next non-empty bucket on the
right adding an offset for each step taken.
> LSH Filter
> ----------
>
> Key: LUCENE-6968
> URL: https://issues.apache.org/jira/browse/LUCENE-6968
> Project: Lucene - Core
> Issue Type: Improvement
> Reporter: Cao Manh Dat
> Assignee: Tommaso Teofili
> Attachments: LUCENE-6968.4.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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