Earticle

초록

영어

It is very important that sellers provide reasonable reserve prices for auction items in internet auction systems. Recently, an agent has been proposed to generate reserve prices automatically based on the case similarity of information retrieval theory and the moving average of time series analysis. However, one problem of the previous approaches is that the recent trend of auction prices is not well reflected on the generated reserve prices, because it simply provides the bid price of the most similar item or an average price of some similar items using the past auction data. In this paper, in order to overcome the problem, we propose a method that generates reserve prices based on the moving average, the exponential smoothing, and the least square of time series analysis. Through performance experiments, we show that the successful bid rate of the new method can be increased by preventing sellers from making unreasonable reserve prices compared with the previous methods.

목차

Abstract
 1. 서론
 2. 관련 연구
  2.1 경매 물품의 낙찰 예정가 결정법
  2.2 시계열 분석
 3. 낙찰 예정가 추천 방법
  3.1 낙찰 예정가 추천 절차
  3.2 시계열 분석에 의한 낙찰 예정 추천 방법
 4. 성능 실험
  4.1 성능 실험 환경
  4.2 실험 결과
 5. 결론 및 향후 연구
 참고문헌

키워드

저자

• 고민정 [ Min Jung Ko | 동국대학교 컴퓨터공학과 박사과정 ]
• 이용규 [ Yong Kyu Lee | 동국대학교 컴퓨터멀티미디어공학과 교수 ] 교신저자

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  JITAM [Journal of Information Technology Applications and Management]

• 간기

  격월간

• pISSN

  1598-6284

• eISSN

  2508-1209

• 수록기간

  1999~2026

• 십진분류

  KDC 005 DDC 005