In this demo we show a recommender system, called SUGGEST, that dynamically generates links to pages that have not yet been visited by a user and might be of his potential interest. Usually other recommender systems exploit a kind of two-phase architecture composed by an off-line component that analyzes Web server access logs and generates information used by a successive online component that generates recommendations. SUGGEST collapse the two-phase into a single on-line Apache module. The component is able to manage very large Web sites made up of dinamically generated pages by means of an efficient LRU-based database management strategy. The demo will show the way SUGGEST is able to anticipate users' requests that will be made farther in the future, introducing a limited overhead on the Web server activity1. © Springer-Verlag Berlin Heidelberg 2004.
CITATION STYLE
Baraglia, R., Merlo, F., & Silvestri, F. (2004). An effective recommender system for highly dynamic and large web sites. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3202, 531–533. https://doi.org/10.1007/978-3-540-30116-5_56
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