Kibitz : a framework for creating recommender systems
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
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| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2018
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| Online Access: | http://hdl.handle.net/1721.1/113103 |
| _version_ | 1826214582713057280 |
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| author | Sun, Brian John |
| author2 | David R. Karger. |
| author_facet | David R. Karger. Sun, Brian John |
| author_sort | Sun, Brian John |
| collection | MIT |
| description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017. |
| first_indexed | 2024-09-23T16:07:46Z |
| format | Thesis |
| id | mit-1721.1/113103 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T16:07:46Z |
| publishDate | 2018 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1131032019-04-11T02:50:30Z Kibitz : a framework for creating recommender systems Framework for creating recommender systems Sun, Brian John David R. Karger. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages 61-62). Recommender 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. by Brian John Sun. M. Eng. 2018-01-12T20:55:53Z 2018-01-12T20:55:53Z 2017 2017 Thesis http://hdl.handle.net/1721.1/113103 1016163732 eng MIT 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. http://dspace.mit.edu/handle/1721.1/7582 72 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Sun, Brian John Kibitz : a framework for creating recommender systems |
| title | Kibitz : a framework for creating recommender systems |
| title_full | Kibitz : a framework for creating recommender systems |
| title_fullStr | Kibitz : a framework for creating recommender systems |
| title_full_unstemmed | Kibitz : a framework for creating recommender systems |
| title_short | Kibitz : a framework for creating recommender systems |
| title_sort | kibitz a framework for creating recommender systems |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/113103 |
| work_keys_str_mv | AT sunbrianjohn kibitzaframeworkforcreatingrecommendersystems AT sunbrianjohn frameworkforcreatingrecommendersystems |