Exploring searcher interactions for distinguishing types of commercial intent

An improved understanding of the relationship between search intent, result quality, and searcher behavior is crucial for improving the effectiveness of web search. While recent progress in user behavior mining has been largely focused on aggregate server-side click logs, we present a new search behavior model that incorporates finegrained user interactions with the search results. We show that mining these interactions, such as mouse movements and scrolling, can enable more effective detection of the user’s search intent. Potential applications include automatic search evaluation, improving search ranking, result presentation, and search advertising. As a case study, we report results on distinguishing between “research” and “purchase” variants of commercial intent, that show our method to be more effective than the current state-of-the-art. Categories and Subject Descriptors H.3.3 [Information Systems]: Information Storage and Retrieval General Terms Design, Experimentati...

• Type: Conference
• Year: 2010
• Where: WWW
• Authors: Qi Guo, Eugene Agichtein
• Keywords: Internet Technology, Search Behavior, Search Intent, User’s Search Intent, WWW 2010