Implementing a content-based recommender system for news readers

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dc.contributor.advisorDu, Weichang
dc.contributor.authorMoattari, Mahta
dc.date.accessioned2023-03-01T16:46:56Z
dc.date.available2023-03-01T16:46:56Z
dc.date.issued2013
dc.date.updated2016-12-13T00:00:00Z
dc.description.abstractRecommender systems are widely used to suggest items to users based on users' interests. Content-based recommender systems are popular, specifically in the area of news services. This report describes the implementation of an effective online news recommender system by combining two different algorithms. Our first algorithm employs users' activity histories as inputs. Then it processes this data using a Bayesian framework to predict users' genuine interests[10], and as a result suggests new articles based on those interests. The other algorithm attempts to find keyword matches among the user's keywords and new articles' keywords to suggest new articles to that user. The Java language was used to implement these algorithms. To test the system, ten different users were chosen randomly among those users who posted comments for more than 50 articles from 2012/05/01 to 2012/07/30. These experiments show that our system successfully suggested new articles to users based on their fields of interest.
dc.description.copyright© Mahta Moattari, 2013
dc.description.noteA Report Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Computer Science in the Graduate Academic Unit of Computer Science Electronic Only. (UNB thesis number) Thesis 9192. (OCoLC) 960905592
dc.description.noteM.C.S., University of New Brunswick, Faculty of Computer Science, 2013.
dc.formattext/xml
dc.format.extentviii, 52 pages
dc.format.mediumelectronic
dc.identifier.oclc(OCoLC) 960905592
dc.identifier.otherThesis 9192
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/14474
dc.language.isoen_CA
dc.publisherUniversity of New Brunswick
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineComputer Science
dc.subject.lcshRecommender systems (Information filtering)
dc.subject.lcshNews audiences.
dc.subject.lcshComputer algorithms.
dc.titleImplementing a content-based recommender system for news readers
dc.typemaster thesis
thesis.degree.disciplineComputer Science
thesis.degree.fullnameMaster of Computer Science
thesis.degree.grantorUniversity of New Brunswick
thesis.degree.levelmasters
thesis.degree.nameM.C.S.

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