Query expansion using gaze-based feedback on the subdocument level

We examine the effect of incorporating gaze-based attention feedback from the user on personalizing the search process. Employing eye tracking data, we keep track of document parts the user read in some way. We use this information on the subdocument level as implicit feedback for query expansion and reranking. We evaluated three different variants incorporating gaze data on the subdocument level and compared them against a baseline based on context on the document level. Our results show that considering reading behavior as feedback yields powerful improvements of the search result accuracy of ca. 32% in the general case. However, the extent of the improvements varies depending on the internal structure of the viewed documents and the type of the current information need. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval--Relevance Feedback General Terms Algorithms, Design, Experimentation, Measurement Keywords Personalizat...

• Type: Journal
• Year: 2008
• Where: SIGIR
• Authors: Georg Buscher, Andreas Dengel, Ludger van Elst
• Keywords: Feedback, Implicit Feedback, Information Technology, SIGIR 2008, Subdocument Level