An approach to effective recommendation considering user preference and diversity simultaneously

Sang Chul Lee, Sang Wook Kim, Sunju Park, Dong Kyu Chae

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper addresses recommendation diversification. Existing diversification methods have difficulty in dealing with the tradeoff between accuracy and diversity. We point out the root of the problem in diversification methods and propose a novel method that can avoid the problem. Our method aims to find an optimal solution of the objective function that is carefully designed to consider user preference and the diversity among recommended items simultaneously. In addition, we propose an item clustering and a greedy approximation to achieve efficiency in recommendation.

Original languageEnglish
Pages (from-to)244-248
Number of pages5
JournalIEICE Transactions on Information and Systems
VolumeE101D
Issue number1
DOIs
Publication statusPublished - 2018 Jan 1

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

Cite this

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An approach to effective recommendation considering user preference and diversity simultaneously. / Lee, Sang Chul; Kim, Sang Wook; Park, Sunju; Chae, Dong Kyu.

In: IEICE Transactions on Information and Systems, Vol. E101D, No. 1, 01.01.2018, p. 244-248.

Research output: Contribution to journalArticle

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