Study of the usefulness of known and new implicit indicators and their optimal combination for accurate inference of users interests

Explicit relevance feedback involves explicit ratings of documents or terms by users and disrupts their browsing and searching. The alternative non-disruptive method is implicit feedback inferring users' needs and interests by monitoring their regular interaction with the system. Some implicit indicators of interest, such as reading time, have been investigated in previous studies and were found indicative to the relevance of documents but not sufficiently accurate [1,2,3,4]. In this paper we present and examine several new relative implicit feedback indicators, and study the effect of combining several implicit indicators. The paper describes a large-scale user study on which users' searches were observed by a specially developed browser that recorded their behavior (implicit indicators) as well as their explicit ratings. We analyzed the relationship between implicit indicators and explicit ratings and found that a certain combination of implicit indicators achieved higher correlation with the explicit ratings than any of the individual indicators. We have also found that the relative indicators are more indicative to the level of interest of a user item than the non-relative indicators.