Towards estimating web search result relevance from touch interactions on mobile devices

Authors:
Qi Guo;Haojian Jin;Dmitry Lagun;Shuai Yuan;Eugene Agichtein
Affiliations:
Microsoft, Redmond, WA, USA;Emory University, Atlanta, Georgia, USA;Emory University, Atlanta, Georgia, USA;Emory University, Atlanta, Georgia, USA;Emory University, Atlanta, Georgia, USA
Venue:
CHI '13 Extended Abstracts on Human Factors in Computing Systems
Year:
2013

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Abstract

Fine-grained search interactions such as mouse cursor movements and scrolling have been shown to be valuable for modeling user attention and preferences of Web search results, in the desktop setting. However, users increasingly search the Web on touch-enabled devices such as smart phones and tablets, where they zoom and swipe instead of mousing and scrolling. In this paper, we present, to our knowledge, the first study of the utility of touch interactions on a mobile devices for estimating Web search result relevance -- which can in turn be used for search result ranking and evaluation. In particular, we explore a variety of touch interaction signals as implicit relevance feedback, based on a user study of 26 users and hundreds of unique Web search queries, result clicks, and page examinations. Our experimental results show that touch interactions provide more effective implicit feedback compared to only the time spent visiting a document, resulting in substantially higher correlation of the estimated document relevance with the explicit relevance judgments.