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https://issues.apache.org/jira/browse/OPENNLP-387?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Boris Galitsky updated OPENNLP-387:
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Attachment: patch.OPENNLP-387.txt
It is now illustrated how to build search engine based on similarity. 3 new
tests are added, including the one which goes to Bing for search and then
re-sorts results based on similarity. Some fixes for the cases of problematic
parsings are done.
> Demonstration on how similarity component improves search accuracy. A query
> is run through Bing search API, and less relevant hits are sorted out by
> similarity measure between the query and the snippet
> ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
>
> Key: OPENNLP-387
> URL: https://issues.apache.org/jira/browse/OPENNLP-387
> Project: OpenNLP
> Issue Type: Improvement
> Components: Similarity
> Affects Versions: 1.6.0
> Reporter: Boris Galitsky
> Assignee: Boris Galitsky
> Attachments: patch.OPENNLP-387.txt
>
> Original Estimate: 48h
> Remaining Estimate: 48h
>
> Right now we use a fancy domain to demonstrate the usability of similarity
> component, such as content generation based on web mining. I believe it also
> makes sense to use a simpler case such as search relevance improvement by use
> of similarity component. We get search candidates by TF*IDF and then apply
> OpenNLP parsing and then Similarity component to assess relevance of a
> snippet to an answer.
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