SIGIR 2009 workshop on understanding the user

Abstract

Modern information search systems can benefit greatly from using additional information about the user and the user's behavior, and research in this area is active and growing. Feedback data based on direct interaction (e.g., clicks, scrolling, etc.) as well as on user profiles/preferences has been proven valuable for personalizing the search process, e.g., from how queries are understood to how relevance is assessed. New technology has made it inexpensive and easy to collect more feedback data and more different types of data (e.g., gaze, emotional, or biometric data). The workshop “Understanding the User – Logging and interpreting user interactions in information search and retrieval” was held in conjunction with the 32nd Annual International ACM SIGIR Conference. It focused on discussing and identifying most promising research directions with respect to logging, interpreting, integrating, and using feedback data. The workshop aimed at bringing together researchers especially from the domains of IR and human-computer interaction interested in the collection, interpretation, and application of user behavior logging for search. Ultimately, one of the main goals was to arrange a commonly shared collection of user interaction logging tools based on a variety of feedback data sources as well as best practices for their usage.