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Facilitating On-line Automated Bargaining Using Data Mining Technology -- A Solution from Time Series Analysis

Bargaining is a frequent activity in the shopping process, and it becomes a trend in electronic trading. In order to facilitate the on-line automatic bargaining activity, we develop three algorithms on the multi-agent system in this thesis. The first algorithm is the pattern generalization algorithm used for generalizing common patterns from transaction records. The second one is the pattern matching algorithm used on-line for identifying possible bargaining patterns from the pattern bases. To deal with the situation that there is no matched pattern, we design the dynamic price issuing algorithm using the utility theory to determine the seller¡¦s price and the timing a deal should be closed. We conducted a series of field experiments to evaluate the proposed algorithms on different seller¡¦s risk perspectives and compared the performance with conventional bargaining methods. The results show that the proposed methods obtain encouraging performance. The major contribution of this research is the initiation efforts on developing data mining algorithms for facilitating the price bargaining process for e-commerce.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0802100-164858
Date02 August 2000
CreatorsKuang-Yi, Chang
ContributorsTing-Pang Liang, Fu-Ren Lin, Chih-Ping Wei
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0802100-164858
Rightsunrestricted, Copyright information available at source archive

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