A large-scale study of user image search behavior on the web

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In this study, we analyze user image search behavior on a large-scale query log from Yahoo Image Search, based on the hypothesis that behavior is dependent on query type. We categorize queries using two orthogonal taxonomies (subjectbased and facet-based) and identify important query types at the intersection of these taxonomies. We study user search behavior on a large-scale set of search sessions for each query type, examining characteristics of sessions, query reformulation patterns, click patterns, and page view patterns. We identify important behavioral differences across query types, in particular showing that some query types are more exploratory, while others correspond to focused search. We also supplement our study with a survey to link the behavioral differences to image search intent. Our findings shed light on the importance of considering query categories to better understand user behavior on image search platforms.
Publisher
ACM Special Interest Group on Computer-Human Interaction (SIGCHI)
Issue Date
2015-04
Language
English
Citation

33rd Annual CHI Conference on Human Factors in Computing Systems, CHI 2015, pp.985 - 994

DOI
10.1145/2702123.2702527
URI
http://hdl.handle.net/10203/314442
Appears in Collection
CS-Conference Papers(학술회의논문)
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