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Fuzzy Bilateral Matchmaking in e-Marketplaces

机译:电子市场的模糊双边配对

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摘要

We present a novel Fuzzy Description Logic (DL) based approach to automate matchmaking in e-marketplaces. We model traders' preferences with the aid of Fuzzy DLs and, given a request, use utility values computed w.r.t. Pareto agreements to rank a set of offers. In particular, we introduce an expressive Fuzzy DL, extended with concrete domains in order to handle numerical, as well as non numerical features, and to deal with vagueness in buyer/seller preferences. Hence, agents can express preferences as e.g., I am searching for a passenger car costing about 22000? yet if the car has a GPS system and more than two-year warranty I can spend up to 25000?. Noteworthy our matchmaking approach, among all the possible matches, chooses the mutually beneficial ones.
机译:我们提出了一种基于新的模糊描述逻辑(DL)方法来自动化电子市场匹配。我们借助模糊DLS模拟交易商的偏好,并给出请求,使用实用价值计算W.R.t.帕累托协议排名一套优惠。特别是,我们引入了一种富有致意模糊的DL,延伸,用混凝土域扩展,以便处理数值以及非数值特征,并在买方/卖方偏好中处理模糊性。因此,代理商可以表达偏好,如例如,我正在寻找大约22000的乘用车成本?然而,如果汽车有GPS系统,并且我可以花费多达25000件以上的保修?值得注意的是我们的匹配方法,在所有可能的匹配中,选择互利的方法。

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