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dc.contributor.authorLi, Tianyien
dc.contributor.authorNakate, Pranaven
dc.contributor.authorSong, Ziqianen
dc.date.accessioned2016-05-10T01:26:53Zen
dc.date.available2016-05-10T01:26:53Zen
dc.date.issued2016-05-04en
dc.identifier.urihttp://hdl.handle.net/10919/70948en
dc.descriptionThere is a complete report describing our tasks, work and evaluation, slides that we used to present our project in class, and code implementation details.en
dc.description.abstractThe students of CS5604 (Information Retrieval and Storage), have been building an Information Retrieval System based on tweet and webpage collections of the Digital Library Research Laboratory (DLRL). The students have been grouped into smaller teams such as Front End team, Solr team, and Collaborative Filtering team, which are building the individual subsystems of the entire project. The teams are collaborating among themselves to integrate their individual subsystems. The Collaborative Filtering (CF) team has been building a recommendation system that can recommend tweets and webpages to users based on content similarity of document pairs as well as user pair similarity. We have finished building the recommendation system so that when the user starts using the system they will be recommended to documents that are similar to those returned by their queries. As more users coming in, they will be also referred to documents that similar users were interested in.en
dc.description.sponsorshipNSF grant IIS - 1319578, III: Small: Integrated Digital Event Archiving and Library (IDEAL).en
dc.language.isoen_USen
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 United Statesen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/en
dc.subjectinformation retrieval and storageen
dc.subjectcollaborative filteringen
dc.subjectrecommendation systemen
dc.titleCollaborative Filtering for IDEALen
dc.typePresentationen
dc.typeSoftwareen
dc.typeTechnical reporten


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Creative Commons Attribution-NonCommercial-NoDerivs 3.0 United States
License: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 United States