【摘要】：在選擇網(wǎng)絡(luò)中介服務(wù)的時(shí)候，信任和信譽(yù)系統(tǒng)的重要性越來越明顯，信任和信譽(yù)系統(tǒng)的商業(yè)應(yīng)用也越來越普級(jí)�？尚拍Ｐ妥鳛楦黝愋湃魏托抛u(yù)系統(tǒng)的核心其基本理念是在某次交易結(jié)束以后，讓參與者為對(duì)方在交易中的表現(xiàn)進(jìn)行評(píng)判，然后用確定的評(píng)判生成信任和信譽(yù)的等級(jí)(可信值)，這個(gè)等級(jí)(可信值)可以幫助其它參與者決定是否與被評(píng)測(cè)者發(fā)生交易行為。目前，此領(lǐng)域內(nèi)的研究者把主要精力放在如何將參與者的評(píng)價(jià)和評(píng)分科學(xué)有效的聚合成可信值，而對(duì)交易中的環(huán)境因素對(duì)交易行為的影響關(guān)注得不夠，事實(shí)上環(huán)境對(duì)行為的影響力是巨大的，可信模型進(jìn)行可信評(píng)估時(shí)應(yīng)該將環(huán)境因素考慮在內(nèi)。 本文提出了一種引入環(huán)境信息的可信評(píng)估模型。本模型首先通過引入傾向度的概念來刻畫被評(píng)估實(shí)體在不同環(huán)境下表現(xiàn)出的不同行為傾向，進(jìn)而提取出實(shí)體在不同環(huán)境下的行為模式。其次將實(shí)體行為模式中的各環(huán)境屬性進(jìn)行有效組合，生成衍生屬性，行為模式擴(kuò)展為擴(kuò)展行為模式，以擴(kuò)展模式來匹配交易環(huán)境，從而找出有特殊傾向性的實(shí)體，，準(zhǔn)確定位最能適應(yīng)當(dāng)前交易環(huán)境的實(shí)體，提高模型應(yīng)對(duì)客戶復(fù)雜需求的能力。最后將與環(huán)境匹配成功的行為模式的傾向度與實(shí)體的一般可信值混調(diào)成環(huán)境敏感可信值。仿真實(shí)驗(yàn)證明，本模型能大幅度的提高用戶的平均效率，具有良好的可用性。
[Abstract]:When choosing network intermediary service, the importance of trust and reputation system is becoming more and more obvious, and the commercial application of trust and reputation system is becoming more and more common. Trust model is the core of all kinds of trust and credit system, whose basic idea is to let the participants judge the performance of each other in the transaction after a transaction. Then a trust and credit rating (trustworthiness) is generated with a deterministic evaluation, which can help other participants decide whether or not to trade with the subject. At present, researchers in this field focus on how to effectively aggregate the participants' evaluation and scoring science into credible values, but pay less attention to the impact of environmental factors on trading behavior. As a matter of fact, the influence of environment on behavior is great, and the environmental factors should be taken into account in the credible assessment of trusted models. In this paper, a trusted assessment model with environmental information is proposed. In this model, the concept of tendency degree is introduced to describe the different behavioral tendencies of the evaluated entity in different environments, and then extract the behavior patterns of the entities in different environments. Secondly, each environment attribute of entity behavior pattern is combined effectively, and the derivative attribute is generated, and the behavior pattern is extended to extend behavior pattern to match the transaction environment, so as to find out the entity with special tendency. Accurately locate the entities that are most suitable for the current trading environment, and improve the ability of the model to deal with the complex needs of customers. Finally, the tendency of the successful behavior pattern matching with the environment is mixed with the general trusted value of the entity to form the environment-sensitive trusted value. The simulation results show that the model can greatly improve the average efficiency of users and has good usability.
【學(xué)位授予單位】：河北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP393.08

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本文編號(hào)：2150811