Apache Solr pp 263-290 | Cite as

Semantic Search

  • Dikshant Shahi

Abstract

You have reached the last chapter of this book, and in this journey you have learned about the significant features of Solr and the nitty-gritty of using it. In previous chapters, you also learned about information retrieval concepts and relevance ranking, which are essential for understanding Solr’s internals and the how and why of scoring. This knowledge is indispensable for what you will be doing most of the time: tuning the document relevance. With all of this information, you should be able to develop an effective search engine that retrieves relevant documents for the query, ranks them appropriately, and provides other features that add to the user experience.

Keywords

Natural Language Processing Semantic Search Relevance Ranking Entity Extraction Semantic Enrichment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Dikshant Shahi 2015

Authors and Affiliations

  • Dikshant Shahi
    • 1
  1. 1.KarnatakaIndia

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