Utilizing query change for session search

Session search is the Information Retrieval (IR) task that performs document retrieval for a search session. During a session, a user constantly modifies queries in order to find relevant documents that fulfill the information need. This paper proposes a novel query change retrieval model (QCM), which utilizes syntactic editing changes between adjacent queries as well as the relationship between query change and previously retrieved documents to enhance session search. We propose to model session search as a Markov Decision Process (MDP). We consider two agents in this MDP: the user agent and the search engine agent. The user agent's actions are query changes that we observe and the search agent's actions are proposed in this paper. Experiments show that our approach is highly effective and outperforms top session search systems in TREC 2011 and 2012.

• Publication year

  2013

• Venue

  Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

• Publication date

  2013-07-28

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1145/2484028.2484055
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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