MASACAD: A multi-agent approach to information customization for the purpose of academic advising of students

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MASACAD: A multi-agent approach to information customization for the purpose of academic advising of students

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dc.contributor.author Hamdi, Mohamed Salah
dc.date.accessioned 2009-12-30T05:55:48Z
dc.date.available 2009-12-30T05:55:48Z
dc.date.issued 2006-02-23
dc.identifier.citation Volume 7, Issue 3, June 2007, Pages 746-771 en_US
dc.identifier.uri http://dx.doi.org/10.1016/j.asoc.2006.02.001
dc.identifier.uri http://hdl.handle.net/10576/10576
dc.description.abstract The growth and advancement in the Internet and the World Wide Web has led to an explosion in the amount of available information. This staggering amount of information has made it extremely difficult for users to locate and retrieve information that is actually relevant to their task at hand. Dealing with this problem of “information overload” will need tools to customize the information space. In this paper we present MASACAD, a multi-agent system that learns to advise students by mining the Web and discuss important problems in relationship to information customization systems and smooth the way for possible solutions. The main idea is to approach information customization using a multi-agent paradigm in combination with a number of aspects from the domains of machine learning, user modeling, and Web mining. en_US
dc.language.iso en en_US
dc.subject Information customization en_US
dc.subject Multi-agents en_US
dc.subject E-Learning en_US
dc.subject Machine learning en_US
dc.subject Neural networks en_US
dc.subject User modeling en_US
dc.subject Web mining en_US
dc.subject Expert systems en_US
dc.title MASACAD: A multi-agent approach to information customization for the purpose of academic advising of students en_US
dc.type Article en_US

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