Supporting revisitation with contextual suggestions

Web browsers provide only little support for users to revisit pages that they do not visit very often. We developed a browser toolbar that reminds users of visited pages related to the page that they currently viewing. The recommendation method combines ranking with propagation methods. A user evaluation shows that on average 22.7% of the revisits were triggered by the toolbar, a considerable change on the participants’ revisitation routines. In this paper we discuss the value of the recommendations and the implications derived from the evaluation.

Venue: JCDL2011

Authors: Ricardo Kawase, George Papadakis and Eelco Herder

PDF: kawase-jcdl2011b

Classification of user interest patterns using a virtual folksonomy

User interest in topics and resources is known to be recurrent and to follow specific patterns, depending on the type of topic or resource. Traditional methods for predicting reoccurring patterns are based on ranking and associative models. In this paper we identify several ‘canonical’ patterns by clustering keywords related to visited resources, making use of a large repository of Web usage data. The keywords are derived from a ‘virtual’ folksonomy of tags assigned to these resources using a collaborative bookmarking system.

Venue: JCDL2011

Authors: Ricardo Kawase and Eelco Herder

PDF: kawase-jcdl2011a