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Title:Automatic detection of search tactic in individual information seeking: A Hidden Markov Model approach
Author(s):Han, Shuguang; Yue, Zhen; He, Daqing
Subject(s):Information seeking behavior
Information Seeking Process
Hidden Markov Model
information behavior
information retrieval
quantitative data analysis
Abstract:Information seeking process is an important research topic in information seeking behavior. Both qualitative and empirical methods have been adopted in analyzing information search processes with major focus on uncovering the latent search tactics behind user behaviors. Most of the existing works require defining search tactics in advance and coding empirical data manually. Among the few works that can recognize usage patterns automatically, they missed explain the latent rationale behind them. In this paper, we proposed an automatic technique and explicitly model the latent search tactics using a Hidden Markov Model. HMM results show that the identified usage patterns of individual information seeking behaviors are consistent with Marchionini’s Information seeking process model. With the advantages of showing the connections between search tactics and search actions, and the transitions among search tactics, we argue that Hidden Markov Model is a useful tool to investigate information seeking process, or at least it provides a feasible method to analyze large scale dataset.
Issue Date:2013-02
Publisher:iSchool
Citation Info:Han, S., Yue, Z., & Daqing H. (2013). Automatic detection of search tactic in individual information seeking: A Hidden Markov Model approach. iConference 2013 Proceedings (pp. 712-716). doi:10.9776/13330
Genre:Conference Poster
Type:Text
Language:English
URI:http://hdl.handle.net/2142/42042
DOI:0.9776/13330
Publication Status:published or submitted for publication
Peer Reviewed:is peer reviewed
Rights Information:Copyright © 2013 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.
Date Available in IDEALS:2013-02-02


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