A single-step approach to recommendation diversification

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper addresses recommendation diversification. Existing diversification methods have a difficulty in dealing with the accuracy-diversity tradeoff. We propose a novel method to simultaneously optimize the user preference and diversity of k-items to be recommended.

Original languageEnglish
Title of host publication26th International World Wide Web Conference 2017, WWW 2017 Companion
PublisherInternational World Wide Web Conferences Steering Committee
Pages809-810
Number of pages2
ISBN (Electronic)9781450349147
DOIs
Publication statusPublished - 2019 Jan 1
Event26th International World Wide Web Conference, WWW 2017 Companion - Perth, Australia
Duration: 2017 Apr 32017 Apr 7

Publication series

Name26th International World Wide Web Conference 2017, WWW 2017 Companion

Other

Other26th International World Wide Web Conference, WWW 2017 Companion
CountryAustralia
CityPerth
Period17/4/317/4/7

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications

Cite this

Lee, S. C., Park, S., Kim, S. W., & Chae, D. K. (2019). A single-step approach to recommendation diversification. In 26th International World Wide Web Conference 2017, WWW 2017 Companion (pp. 809-810). (26th International World Wide Web Conference 2017, WWW 2017 Companion). International World Wide Web Conferences Steering Committee. https://doi.org/10.1145/3041021.3054220
Lee, Sang Chul ; Park, Sunju ; Kim, Sang Wook ; Chae, Dong Kyu. / A single-step approach to recommendation diversification. 26th International World Wide Web Conference 2017, WWW 2017 Companion. International World Wide Web Conferences Steering Committee, 2019. pp. 809-810 (26th International World Wide Web Conference 2017, WWW 2017 Companion).
@inproceedings{6a1ccca4a2fc4f66832330216a3b8485,
title = "A single-step approach to recommendation diversification",
abstract = "This paper addresses recommendation diversification. Existing diversification methods have a difficulty in dealing with the accuracy-diversity tradeoff. We propose a novel method to simultaneously optimize the user preference and diversity of k-items to be recommended.",
author = "Lee, {Sang Chul} and Sunju Park and Kim, {Sang Wook} and Chae, {Dong Kyu}",
year = "2019",
month = "1",
day = "1",
doi = "10.1145/3041021.3054220",
language = "English",
series = "26th International World Wide Web Conference 2017, WWW 2017 Companion",
publisher = "International World Wide Web Conferences Steering Committee",
pages = "809--810",
booktitle = "26th International World Wide Web Conference 2017, WWW 2017 Companion",

}

Lee, SC, Park, S, Kim, SW & Chae, DK 2019, A single-step approach to recommendation diversification. in 26th International World Wide Web Conference 2017, WWW 2017 Companion. 26th International World Wide Web Conference 2017, WWW 2017 Companion, International World Wide Web Conferences Steering Committee, pp. 809-810, 26th International World Wide Web Conference, WWW 2017 Companion, Perth, Australia, 17/4/3. https://doi.org/10.1145/3041021.3054220

A single-step approach to recommendation diversification. / Lee, Sang Chul; Park, Sunju; Kim, Sang Wook; Chae, Dong Kyu.

26th International World Wide Web Conference 2017, WWW 2017 Companion. International World Wide Web Conferences Steering Committee, 2019. p. 809-810 (26th International World Wide Web Conference 2017, WWW 2017 Companion).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - A single-step approach to recommendation diversification

AU - Lee, Sang Chul

AU - Park, Sunju

AU - Kim, Sang Wook

AU - Chae, Dong Kyu

PY - 2019/1/1

Y1 - 2019/1/1

N2 - This paper addresses recommendation diversification. Existing diversification methods have a difficulty in dealing with the accuracy-diversity tradeoff. We propose a novel method to simultaneously optimize the user preference and diversity of k-items to be recommended.

AB - This paper addresses recommendation diversification. Existing diversification methods have a difficulty in dealing with the accuracy-diversity tradeoff. We propose a novel method to simultaneously optimize the user preference and diversity of k-items to be recommended.

UR - http://www.scopus.com/inward/record.url?scp=85060290678&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85060290678&partnerID=8YFLogxK

U2 - 10.1145/3041021.3054220

DO - 10.1145/3041021.3054220

M3 - Conference contribution

AN - SCOPUS:85060290678

T3 - 26th International World Wide Web Conference 2017, WWW 2017 Companion

SP - 809

EP - 810

BT - 26th International World Wide Web Conference 2017, WWW 2017 Companion

PB - International World Wide Web Conferences Steering Committee

ER -

Lee SC, Park S, Kim SW, Chae DK. A single-step approach to recommendation diversification. In 26th International World Wide Web Conference 2017, WWW 2017 Companion. International World Wide Web Conferences Steering Committee. 2019. p. 809-810. (26th International World Wide Web Conference 2017, WWW 2017 Companion). https://doi.org/10.1145/3041021.3054220