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AuthorHamdi, Mohamed Salah
Available date2009-12-30T05:55:48Z
Publication Date2006-02-23
Publication NameApplied Soft Computing
Identifierhttp://dx.doi.org/10.1016/j.asoc.2006.02.001
CitationMohamed Salah Hamdi, MASACAD: A multi-agent approach to information customization for the purpose of academic advising of students, Applied Soft Computing, Volume 7, Issue 3, June 2007, Pages 746-771
URIhttp://hdl.handle.net/10576/10576
AbstractThe 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.
Languageen
PublisherElsevier B.V.
SubjectInformation customization
SubjectMulti-agents
SubjectE-Learning
SubjectMachine learning
SubjectNeural networks
SubjectUser modeling
SubjectWeb mining
SubjectExpert systems
TitleMASACAD: A multi-agent approach to information customization for the purpose of academic advising of students
TypeArticle


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