This paper examines the reliability of implicit feedback generated from clickthrough data in WWW search. Analyzing the users’ decision process using eyetracking and comparing im...
Thorsten Joachims, Laura A. Granka, Bing Pan, Hele...
Evaluating user preferences of web search results is crucial for search engine development, deployment, and maintenance. We present a real-world study of modeling the behavior of ...
Eugene Agichtein, Eric Brill, Susan T. Dumais, Rob...
Implicit feedback algorithms utilize interaction between searchers and search systems to learn more about users’ needs and interests than expressed in query statements alone. Th...
A common task of recommender systems is to improve customer experience through personalized recommendations based on prior implicit feedback. These systems passively track differe...
We examine two basic sources for implicit relevance feedback on the segment level for search personalization: eye tracking and display time. A controlled study has been conducted ...
We introduce GaZIR, a gaze-based interface for browsing and searching for images. The system computes on-line predictions of relevance of images based on implicit feedback, and wh...
In order to help users navigate an image search system, one could provide explicit information on a small set of images as to which of them are relevant or not to their task. Thes...
The availability of map interfaces and location-aware devices makes a growing amount of unstructured, geo-referenced information available on the Web. In particular, over twelve m...