Show simple item record

dc.contributor.advisorDavid R. Karger.en_US
dc.contributor.authorSun, Brian Johnen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2018-01-12T20:55:53Z
dc.date.available2018-01-12T20:55:53Z
dc.date.copyright2017en_US
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/113103
dc.descriptionThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 61-62).en_US
dc.description.abstractRecommender systems are one of the most vital and ubiquitous parts of the modern web. They are used by many major internet services such as Facebook, Google, and Amazon. However, there is a wealth of content and data that remains untapped by mainstream commercial recommender systems. We have designed and implemented Kibitz, a framework that allows anyone to create a recommender system on top of an arbitrary collection of items. We have developed a web application that facilitates the creation, customization and deployment of standalone websites for browsing and rating items as well as receiving item recommendations. We have also created a set of libraries for embedding rating and recommendation functionality into other websites. Partnering with local bookstores, we evaluated the process of using Kibitz to build recommender systems for their communities.en_US
dc.description.statementofresponsibilityby Brian John Sun.en_US
dc.format.extent72 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleKibitz : a framework for creating recommender systemsen_US
dc.title.alternativeFramework for creating recommender systemsen_US
dc.typeThesisen_US
dc.description.degreeM. Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc1016163732en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record