Comparing Two Strategies for Query Expansion in a News Monitoring System

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• 关键词：Query analysis ; Query expansion ; Web IR and social media search
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9612
• 期：1
• 页码：267-275
• 全文大小：315 KB
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• 作者单位：Parvaz Mahdabi (18)
  Andrei Popescu-Belis (18)
  
  18. Idiap Research Institute, Martigny, Switzerland
  
• 丛书名：Natural Language Processing and Information Systems
• ISBN：978-3-319-41754-7
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9612

文摘

In this paper, we study query expansion strategies that improve the relevance of retrieved documents in a news and social media monitoring system, which performs real-time searches based on complex queries. We propose a two-step retrieval strategy using textual features such as bi-gram word dependencies, proximity, and expansion terms. We compare two different methods for query expansion: (1) based on word co-occurrence information; (2) using semantically-related expansion terms. We evaluate our methods and compare them with the baseline version of the system by crowdsourcing user-centric tasks. The results show that word co-occurrence outperforms semantic query expansion, and improves over the baseline in terms of relevance and utility.