elasticsearch-vector-scoring | Score documents with pure dot product | Machine Learning library
kandi X-RAY | elasticsearch-vector-scoring Summary
kandi X-RAY | elasticsearch-vector-scoring Summary
The aim of this plugin is to enable real-time scoring of vector-based models, in particular factor-based recommendation models. In this case, user and item factor vectors are indexed using the Delimited Payload Token Filter, e.g. the vector [1.2, 0.1, 0.4, -0.2, 0.3] is indexed as a string: 0|1.2 1|0.1 2|0.4 3|-0.2 4|0.3. This stores the vector indices as "terms" and the vector values as "payloads".
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Top functions reviewed by kandi - BETA
- Performs the score query
- The native script factory
elasticsearch-vector-scoring Key Features
elasticsearch-vector-scoring Examples and Code Snippets
Community Discussions
Trending Discussions on elasticsearch-vector-scoring
QUESTION
We're trying to replicate this ES plugin https://github.com/MLnick/elasticsearch-vector-scoring. The reason is AWS ES doesn't allow any custom plugin to be installed. The plugin is just doing dot product and cosine similarity so I'm guessing it should be really simple to replicate that in painless
script. It looks like groovy
scripting is deprecated in 5.0.
Here's the source code of the plugin.
...ANSWER
Answered 2017-May-09 at 18:29Option 1
Due to the fact that @model_factor is a text
field, in painless scripting, it would be possible to access it, setting fielddata=true in the mapping. So the mapping should be:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install elasticsearch-vector-scoring
Start Elasticsearch: ELASTIC_HOME/bin/elasticsearch. You should see the plugin registered at Elasticsearch startup:.
Build: mvn package
Install plugin in Elasticsearch: ELASTIC_HOME/bin/elasticsearch-plugin install file:///PROJECT_HOME/target/releases/elasticsearch-vector-scoring-5.4.0.zip (stop ES first).
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