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Sport News Semantic Search with Natural Language Questions

  • Quang-Minh NguyenEmail author
  • Son-Hong Ngo
  • Tuan-Dung Cao
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 257)

Abstract

An increasingly huge amount of sport news published from a number of heterogeneous sources on the Web brings challenges to the traditional searching method using keywords. Providing an expressive way to retrieve news items and exploiting the advantages of semantic search technique in the development of Web-based sports news aggregation system is within our consideration. This paper presents a method to translate natural language questions into queries in SPARQL, the standard query language recommended by W3C for semantic data. Our contribution consists mainly of the construction of a semantic model representing a question, the detection of ontology vocabularies and knowledge base elements in question, and their mapping to generate a query. We evaluate the method based on a set of natural language questions and the results show that the proposed method achieves good performance with respect to precision.

Keywords

Natural language interface Semantic web Question answering Sport news aggregator SPARQL 

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  • Quang-Minh Nguyen
    • 1
    Email author
  • Son-Hong Ngo
    • 2
  • Tuan-Dung Cao
    • 2
  1. 1.School of Electronics and TelecommunicationsHanoi University of Science and TechnologyHanoiVietnam
  2. 2.School of Information and Communication TechnologyHanoi University of Science and TechnologyHanoiVietnam

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