Earticle

초록

영어

More and more customers are buying products on on-line stores and they will be able to make a decision to buy with ease, if they are given reliable information of sellers. But unfortunately, such information is not available and very limited at best. Thus, this paper proposes a recommendation system which recommends most dependable sellers to the customers who want to buy a product. The system first evaluates the sellers registered on an online store by classifying them either as good or as bad using a decision tree technique (J48), and selects only good sellers. Then, the system makes use of the content-based filtering method to find best-matching top-K sellers among the selected good sellers by comparing the individual seller profile and the customer profile. This study makes a contribution in that to our knowledge, it is the first attempt to recommend sellers to customers, not products as is done in other studies.

목차

Abstract
 1. Introduction
 2. Literature review
  2.1 Credit scoring
  2.2 Content-Based Filtering
 3. Experiment
  3.1 Data description
  3.2 Overall Procedure of the proposed sellerrecommendation system
 4. Experimental results
  4.1 Results from classification of trustworthysellers
  4.2 Results for seller recommendation
 5. Conclusion
 References

키워드

저자

• Seungsup Lee [ Business School, Korea University ]
• Yongmoo Suh [ Business School, Korea University, ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국경영정보학회 정기 학술대회 [KMIS Conference]

• 간기

  반년간

• 수록기간

  1990~2025

• 십진분류

  KDC 325 DDC 658