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A Min-Max Distance-based Preference Boundary Applied for Recommending New Items

첫 페이지 보기
  • 발행기관
    한국경영정보학회 바로가기
  • 간행물
    한국경영정보학회 정기 학술대회 바로가기
  • 통권
    KMIS & Conf-IRM International Conference 2011 (2011.06)바로가기
  • 페이지
    pp.473-483
  • 저자
    Hyea Kyeong Kim, Min Kyu Jung, Moon Kyoung Jang, Jae Kyeong Kim
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A145568

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원문정보

초록

영어
When new items are released, it is necessary to promote these items. In this situation, a recommender system specializing in new items can help item providers find potential customers. This study aims to develop a preference boundary-based procedure for recommending new items. The basic principle is that if a new item belongs within the preference boundary of a target customer, then it is evaluated to be preferred by the customer. The new item recommendation procedure is organized in the following two phases. The first phase defines each customer’ preference boundary, and the second phase decides the target customer set for recommending new items. In this research, customer’preferences and item characteristics including new items are represented in a feature space. And the scope of boundary of the target customer’ preference is extended to those of neighbors’ Furthermore, compared to existing recommender systems, the suggested procedure aims to find target customers for the new released items. Diverse algorithms are suggested for the procedure, and their effectiveness scores are measured and compared through a series of experiments with a real mobile image transaction data set. The experiment results are compared, and discussions about the results are also given with a further research opportunity.

목차

Abstract
 1. Introduction
 2. Related Work
  2.1 Recommendation Systems
  2. 2 A New Item Recommendation
 3. METHODOLOGY
  3.1 Overall Procedure
  3.2 Representation of Preference Boundary
  3.3 Range of Preference Boundary
  3.4 Neighbor Formation
  3.5 Phase 1: Defining Each Customer’s Preference Boundary
  3.6 Phase 2: Finding Target Customers to Recommend New Items
 4. Experiment
  4.1 The Data Set
  4.2 Measures and Experimental Environment
  4.3 Results and Discussion
 5. Conclusions
 Acknowledgment
 References

키워드

Recommender System; Collaborative Filtering; Multimedia Content; Personalization

저자

  • Hyea Kyeong Kim [ School of Management, Kyunghee University ]
  • Min Kyu Jung [ School of Management, Kyunghee University ]
  • Moon Kyoung Jang [ School of Management, Kyunghee University ]
  • Jae Kyeong Kim [ School of Management, Kyunghee University, ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    한국경영정보학회 [The Korea Society of Management information Systems]
  • 설립연도
    1989
  • 분야
    사회과학>경영학
  • 소개
    이 학회는 경영정보학의 연구 및 교류를 촉진하고 학문의 발전과 응용에 공헌함을 목적으로 합니다.

간행물

  • 간행물명
    한국경영정보학회 정기 학술대회 [KMIS Conference]
  • 간기
    반년간
  • 수록기간
    1990~2025
  • 십진분류
    KDC 325 DDC 658

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