NDLI: Modeling and predicting information search behavior

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Modeling and predicting information search behavior

Content Provider	ACM Digital Library
Author	Fu, Wai Tat Chin, Jessie Chevalier, Aline Karanam, Saraschandra Sanchiz, Mylène van Oostendorp, Herre
Abstract	This paper looks at two limitations of cognitive models of web-navigation: first, they do not account for the entire process of information search and second, they do not account for the differences in search behavior caused by aging. To address these limitations, data from an experiment in which two types of information search tasks (simple and difficult), presented to both young and old participants was used. We found that in general difficult tasks demand significantly more time, significantly more clicks, significantly more reformulations and are answered significantly less accurately than simple tasks. Older persons inspect the search engine result pages significantly longer, produce significantly fewer reformulations with difficult tasks than younger persons, and are significantly more accurate than younger persons with simple tasks. We next used a cognitive model of web-navigation called CoLiDeS to predict which search engine result a user would choose to click. Old participants were found to click more often only on search engine results with high semantic similarity with the query. Search engine results generated by old participants were of higher semantic similarity value (computed w.r.t the query) than those generated by young participants only in the second cycle. Match between model-predicted clicks and actual user clicks was found to be significantly higher for difficult tasks compared to simple tasks. Potential improvements in enhancing the modeling and its applications are discussed.
Starting Page	1
Ending Page	12
Page Count	12
File Format	PDF
ISBN	9781450332934
DOI	10.1145/2797115.2797123
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-07-13
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Cognitive factors Aging Information search Modeling
Content Type	Text
Resource Type	Article

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