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Understanding "Abandoned" Ads: Towards Personalized Commercial Intent Inference via Mouse Movement Analysis
 

Summary: Understanding "Abandoned" Ads: Towards Personalized
Commercial Intent Inference via Mouse Movement Analysis
Qi Guo, Eugene Agichtein
Emory University, United States
{qguo3, eugene}@mathcs.emory.edu
Charles L. A. Clarke, Azin Ashkan
University of Waterloo, Canada
{claclark, aashkan}@cs.uwaterloo.ca
ABSTRACT
Clickthrough on ads and search results have been success-
fully used to infer user interest and preferences, but these
indicators are typically most effective for modeling the"dom-
inant" or most popular intent for a query. In this paper we
begin to explore rich client-side instrumentation for inferring
personalized commercial intent of users. In particular, we in-
vestigate whether mouse movement over search results can
provide clues into the users' intent. As one practical applica-
tion, we attempt to understand the causes of "abandoned"
-- unclicked -- ads: that is, to automatically distinguish
whether a user's search had no commercial intent at all, or

  

Source: Agichtein, Eugene - Department of Mathematics and Computer Science, Emory University

 

Collections: Computer Technologies and Information Sciences