Diversification in Recommendation System

Toppo, Manjela and Desarkar, Maunendra Sankar (2018) Diversification in Recommendation System. Masters thesis, Indian Institute of Technology Hyderabad.

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Diversification in Recommendation system However, if it shows many similar items that might become monotonous for the user To handle this scenario is to diversify the recommended list. Di- versification helps in recommendation without data(cold start problem) .Diversification maintain the trade off between popularity, freshness and relevance items. In real time Diversification helps in better coverage of items in the recommendation list. It can give emphasis to both novelty and relevance. Novelty means items that contain new information when compared to previously seen ones and covers all the topics. Relevance include top ranked item of the search results.

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IITH Creators:
IITH CreatorsORCiD
Desarkar, Maunendra SankarUNSPECIFIED
Item Type: Thesis (Masters)
Uncontrolled Keywords: Novelty, Diversity
Subjects: Computer science
Depositing User: Team Library
Date Deposited: 29 Jun 2018 11:02
Last Modified: 29 Jun 2018 11:02
URI: http://raiith.iith.ac.in/id/eprint/4104
Publisher URL:
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