Comparing User Approach to Complex Information Needs in Traditional Web Search and Conversational Search

Bachelor Thesis (2020)
Author(s)

L.G. Leibbrandt (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

C Hauff – Mentor (TU Delft - Web Information Systems)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2020 Louise Leibbrandt
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Louise Leibbrandt
Graduation Date
22-06-2020
Awarding Institution
Delft University of Technology
Project
['CSE3000 Research Project']
Programme
['Computer Science and Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Conversational search systems have recently gained popularity due to their effectiveness in performing small tasks and answering factoid questions. However, under complex search scenarios, these systems fail and fall back to techniques used by traditional search engines. As tasks requiring user learning are inherently complex, user knowledge is a powerful indicator of system performance under complex search and user ability to successfully interact with the information content. We present a study in which user knowledge gain and query formulation is explored in both the traditional web search and conversational search formats. Through crowd sourcing, 50 participants were recruited and conducted complex search sessions on either the traditional or conversational search medium. Through the use of a knowledge test given to the participant both before and after the search session, knowledge gain was determined. Furthermore, session queries and timestamps were tracked. It is found that participants have a significantly higher knowledge gain in traditional search, while conversational search sessions tended to have a higher number of queries and average query length.

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