Toppo, Manjela and Desarkar, Maunendra Sankar
(2018)
Diversification in Recommendation System.
Masters thesis, Indian Institute of Technology Hyderabad.
Abstract
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 Creators | ORCiD |
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Desarkar, Maunendra Sankar | UNSPECIFIED |
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Item Type: |
Thesis
(Masters)
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Uncontrolled Keywords: |
Novelty, Diversity |
Subjects: |
Computer science |
Depositing User: |
Team Library
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Date Deposited: |
29 Jun 2018 11:02 |
Last Modified: |
29 Jun 2018 11:02 |
URI: |
http://raiithold.iith.ac.in/id/eprint/4104 |
Publisher URL: |
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Related URLs: |
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