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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2015/05/18 23:06:03 UTC
[jira] [Assigned] (SPARK-7618) Word2VecModel cache normalized
wordVectors to speed up findSynonyms
[ https://issues.apache.org/jira/browse/SPARK-7618?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-7618:
-----------------------------------
Assignee: Apache Spark
> Word2VecModel cache normalized wordVectors to speed up findSynonyms
> -------------------------------------------------------------------
>
> Key: SPARK-7618
> URL: https://issues.apache.org/jira/browse/SPARK-7618
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.3.1
> Reporter: Eric Li
> Assignee: Apache Spark
> Priority: Minor
> Original Estimate: 2h
> Remaining Estimate: 2h
>
> In current implementation, each findSynonyms call will need to do a Euclidean Normalization (cosineVec / wordVecNorms), this is expensive. Caching a copy of normalized wordVectors will speed up multiple findSynonyms call. This is how the Google's word2vec C code implemented.
> In addition, doing a lazy loading for wordVectors will be nice as well.
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