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Preference Elicitation of the NSS in the Ecommerce

机译:电子商务中NSS的优先启发

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Electronic negotiations are becoming an important research subject in the area of electronic commerce. Decision analysis and especially multiattributive utility theory play an important role for the support of electronic negotiations. Decision theory is a well-tested approach to helping a user choose from a set of alternatives when the user’s preference structure is known. The preferences are usually represented as a utility function on the set of alternatives such that the user prefers an alternative exactly when it has higher utility. In cases where the utility function is unknown or partially known, it must be elicited from the user in order for decision theory to be applicable, and this can often be a timeconsuming process that has unknown payoff for the user. Understanding and representing a user’s preferences accurately is a crucial element of most decision support systems, since users have a bounded rationality, such complex processes will never be strictly linear nor rational. Therefore, there are a number of challenges that NSS has to meet. This paper discusses the challenges and evaluates different methods for preference elicitation with respect to these challenges. To choice the appropriate preferences elicitation method and to guess the opponent’s preferences can overcome the specific challenges of preference elicitation in NSS which will be suitable for dynamic ecommerce.
机译:电子谈判正在成为电子商务领域的重要研究课题。决策分析,尤其是多属性效用理论在支持电子谈判中发挥着重要作用。决策理论是一种经过实践检验的方法,可以在用户的​​偏好结构已知时帮助用户从一组备选方案中进行选择。偏好通常被表示为一组备选方案上的效用函数,使得用户在具有更高效用时正好偏爱该备选方案。在效用函数未知或部分已知的情况下,必须从用户处得出效用,才能应用决策理论,并且这通常是一个耗时的过程,对用户而言是未知的回报。准确地理解和表示用户的偏好是大多数决策支持系统的关键要素,因为用户具有有限的理性,所以这种复杂的过程永远不会是严格的线性或理性的。因此,NSS必须面对许多挑战。本文讨论了这些挑战,并针对这些挑战评估了不同的偏好激发方法。选择适当的偏好激发方法并猜测对手的偏好可以克服NSS中适合动态电子商务的偏好激发的特定挑战。

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