Implicit search feature based approach to assist users in exploratory search tasks

Chathra Hendahewa, Chirag Shah

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Analyzing and modeling users' online search behaviors when conducting exploratory search tasks could be instrumental in discovering search behavior patterns that can then be leveraged to assist users in reaching their search task goals. We propose a framework for evaluating exploratory search based on implicit features and user search action sequences extracted from the transactional log data to model different aspects of exploratory search namely uncertainty, creativity, exploration, and knowledge discovery. We show the effectiveness of the proposed framework by demonstrating how it can be used to understand and evaluate user search performance and thereby make meaningful recommendations to improve the overall search performance of users. We used data collected from a user study consisting of 18 users conducting an exploratory search task for two sessions with two different topics in the experimental analysis. With this analysis we show that we can effectively model their behavior using implicit features to predict the user's future performance level with above 70% accuracy in most cases. Further, using simulations we demonstrate that our search process based recommendations improve the search performance of low performing users over time and validate these findings using both qualitative and quantitative approaches.

Original languageEnglish (US)
Pages (from-to)643-661
Number of pages19
JournalInformation Processing and Management
Volume51
Issue number5
DOIs
StatePublished - Jun 20 2015

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Media Technology
  • Computer Science Applications
  • Management Science and Operations Research
  • Library and Information Sciences

Keywords

  • Evaluation
  • Exploratory search
  • Implicit features
  • User behavior

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