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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/52152

    Title: 一套線上拍賣之基因式模糊名聲推理方法
    Other Titles: A genetic fuzzy reputation inference method for on-line auctions
    Authors: 張鴻文;Chang, Hung-wen
    Contributors: 淡江大學資訊管理學系碩士班
    Keywords: 名聲管理(reputation management);模糊推理(fuzzy inference);基因演算法(genetic algorithm);線上拍賣(online auction);reputation management;Fuzzy inference;Genetic Algorithm;Online Auction
    Date: 2010
    Issue Date: 2010-09-23 16:58:00 (UTC+8)
    Abstract: 隨著網路的普及化與「宅經濟」的促使之下,網路線上拍賣系統的業績也不斷攀升。以eBay為例,2007年的網拍業務收入為59.7億美元,而在2010年該預估可能將達到88億美元至91億美元,顯示線上拍賣的蓬勃發展。然而,拍賣網站會員人數動輒百萬計,如何協助使用者在下標前挑選合適的賣家便成為重要課題。目前,網拍平台大多使用二元名聲系統(binary reputation system)來管理交易者的名聲,雖然簡單易懂,但很難從中獲得完整的名聲參考資訊。 有鑑於此,學者們紛紛提出各種不同的名聲計算方式,以協助使用者挑選合適賣家。
    Because of the universal usage of internet, a name "Otaku Economy" appears. An online auction system''s sales increases continual. Take the leader of this online auction systems-eBay for instance. The revenues of auction sales are 5.97 billion dollars in 2007, and the estimation revenues of eBay will reach from 8.8 billion dollars to 9.1 billion dollars. The above-mentioned facts indicate that those users who use the online auction system to trade with others are increasing. The most important issue are how to choose an appropriate auctioneer and an auction website''s members are tens of thousands that cause the difficulties of management. The auction websites use binary reputation management now to manage the auctioneer''s reputation, but still can''t offer entire reputation information. Because of the drawbacks of binary reputation, many scholars announce different calculation of reputation to help users choosing the right auctioneer.
    In order to help users solving above-mentioned problems, this thesis develop a suit of Genetic Fuzzy Reputation Inference Method- GFRep for On-Line Auctions .To offer more perfect calculation methods, this research think about three factors including "deal-time" ,"deal-amount" and "the credit of dependability". We calculate total reputation value by fuzzy inference. To strengthen the efficiency of fuzzy rules, We use genetic algorithm to create fuzzy rule base optimizing the rule''s consequent and fuzzy variable''s membership function. To validate the system''s effectiveness, we gather the transaction information from eBay. The result reveals that GFRep is more reliable than other three methods.
    Appears in Collections:[資訊管理學系暨研究所] 學位論文

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