IBM/improve-discovery-results-using-api-based-relevancy-training
Improve Discovery results using programmatic (api) relevancy training
This project helps developers and data scientists improve the accuracy of search results from IBM Watson Discovery. By programmatically providing feedback on which results are most relevant to specific queries, the system learns and reorders future search results, placing the most helpful information at the top. This is ideal for those who manage large-scale content collections and need to fine-tune search precision.
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Use this if you have a large number of natural language queries and documents in Watson Discovery and need to programmatically train the service to return more relevant search results.
Not ideal if your existing Watson Discovery search results already meet your needs or if you prefer to perform relevancy training manually through a graphical user interface.
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9
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10
Language
Python
License
Apache-2.0
Category
Last pushed
Sep 17, 2025
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