A Decision-Guided Group Package Recommender Based on Multi-Criteria Optimization and Voting

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dc.contributor.advisorBrodsky, Alexander
dc.contributor.authorMengash, Hanan Abdullah
dc.creatorMengash, Hanan Abdullah
dc.date.accessioned2016-09-28T10:23:52Z
dc.date.available2016-09-28T10:23:52Z
dc.date.issued2016
dc.description.abstractRecommender systems are intended to help users make effective product and service choices, especially over the Internet. They are used in a variety of applications and have proven to be valuable for predicting the utility or relevance of a particular item and for providing personalized recommendations. State-of-the-art recommender systems focus on atomic (single) products or services and on individual users. This dissertation considers three ways of extending recommender systems: (1) to make composite (package) rather than atomic recommendations; (2) to use multiple rather than single criteria for recommendations; and, most importantly, (3) to support groups of diverse users or decision makers who might have different, even strongly conflicting, views on the weights of different criteria.
dc.format.extent164 pages
dc.identifier.urihttps://hdl.handle.net/1920/10475
dc.language.isoen
dc.rightsCopyright 2016 Hanan Abdullah Mengash
dc.subjectComputer science
dc.subjectInformation technology
dc.subjectArtificial intelligence
dc.subjectDecision guidance
dc.subjectGroup decision-making
dc.subjectGroup recommender system
dc.subjectMulti-criteria optimization
dc.subjectPackage recommendations
dc.subjectRenewable energy sources investment
dc.titleA Decision-Guided Group Package Recommender Based on Multi-Criteria Optimization and Voting
dc.typeDissertation
thesis.degree.disciplineComputer Science
thesis.degree.grantorGeorge Mason University
thesis.degree.levelPh.D.

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