title: An Adaptive Web Page Recommendation Service
creator: Balabanovic, Marko
subject: Digital Libraries
description: An adaptive recommendation service seeks to adapt to its users, providing increasingly personalized recommendations over time. In this paper we introduce the "Fab" adaptive web page recommendation service. There has been much research on analyzing document content in order to improve recommendations or search results. More recently researchers have begun to explore how the similarities between users can be exploited to the same ends. The Fab system strikes a balance between these two approaches, taking advantage of the shared interests among users without losing the benefits of the representations provided by content analysis. Running since March 1996, it has been populated with a collection of agents for the collection and selection of web pages, whose interaction fosters emergent collaborative properties. In this paper we explain the design of the system architecture and report the results of our first experiment, evaluating recommendations provided to a group of test users. 
publisher: Stanford InfoLab
date: 2000-01-18
type: Techreport
type: NonPeerReviewed
format: application/pdf
identifier: http://ilpubs.stanford.edu:8090/461/1/2000-40.pdf
identifier: Balabanovic, Marko (2000) An Adaptive Web Page Recommendation Service. Technical Report. Stanford InfoLab. (Publication Note: Revision appears in First International Conference on Autonomous Agents, February 1997, Marina del Rey CA)
relation: http://ilpubs.stanford.edu:8090/461/