Description
Currently, recommender systems are used extensively to find the right audience with the "right" content over various platforms. Recommendations generated by these systems aim to offer relevant items to users. Different approaches have been suggested to solve this problem mainly by using the rating history of the user or by identifying the preferences of similar users.
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Contributors
- Sargar, Rushikesh Bapu (Author)
- Atkinson, Robert K (Thesis advisor)
- Chen, Yinong (Thesis advisor)
- Chavez-Echeagaray, Maria Elena (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2020
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Note
- Masters Thesis Computer Science 2020