Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/6715
Title: A Multi-Agent Recommender System
Authors: Alípio Jorge
Eugénio Oliveira
Jorge Morais
Issue Date: 2012
Abstract: The large amount of pages in Websites is a problem for users who waste time looking for the information they really want. Knowledge about users' previous visits may provide patterns that allow the customization of the Website. This concept is known as Adaptive Website: a Website that adapts itself for the purpose of improving the user's experience. Some Web Mining algorithms have been proposed for adapting a Website. In this paper, a recommender system using agents with two different algorithms (associative rules and collaborative filtering) is described. Both algorithms are incremental and work with binary data. Results show that this multi-agent approach combining different algorithms is capable of improving user's satisfaction.
URI: http://repositorio.inesctec.pt/handle/123456789/6715
http://dx.doi.org/10.1007/978-3-642-28765-7_33
metadata.dc.type: conferenceObject
Publication
Appears in Collections:LIAAD - Articles in International Conferences

Files in This Item:
File Description SizeFormat 
PS-08396.pdf651.42 kBAdobe PDFThumbnail
View/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.