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Improving Semantic Search through Entity-Based Document Ranking

Published: 13 July 2015 Publication History

Abstract

Traditional keyword-based IR approaches take into account the document context only in a limited manner. In our paper we present a novel document ranking approach based on the semantic relationships between named entities. In the first step we annotate all documents with named entities from a knowledge base (for example people, places and organisations). In the next step these annotations in combination with the relationships from the knowledge base are used to rank documents in order to perform a semantic search. Documents that contain the specific named entity that was searched for as well as other strongly related entities, receive a higher ranking. The inclusion of the document context in the ranking approach achieves a higher precision in the Top-K results.

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      WIMS '15: Proceedings of the 5th International Conference on Web Intelligence, Mining and Semantics
      July 2015
      176 pages
      ISBN:9781450332934
      DOI:10.1145/2797115
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      • WNRI: Western Norway Research Institute
      • University of Cyprus

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      Association for Computing Machinery

      New York, NY, United States

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      Published: 13 July 2015

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      Author Tags

      1. document ranking
      2. information retrieval
      3. named entity recognition
      4. relation ranking
      5. semantic search

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