中文摘要：

网络环境下专家根据个人的偏好对备选期刊给出不同形式的偏好信息，因此有必要研究基于不同偏好信息的科技期刊选订方法。本文讨论了4种不同形式的偏好信息，包括直接反映备选期刊优劣次序的序关系值和效用值的信息，也包括间接反映备选期刊优劣次序的成对比较互反判断矩阵和模糊互补判断矩阵的信息。首先给出了序关系值、互反判断矩阵和模糊互补判断矩阵3种偏好信息均转化为效用值形式的计算公式，然后从相对熵的概念出发，提出了一种相对熵最优化的信息集成模型，给出了模型的解。文中进行了实例分析，结果表明本文提出的集成方法是有效的。

英文摘要：

The experts usually give their different preference information about periodicals to be subscribed to in the network environment according to their preference. Therefore it＇ s necessary to study the sci-teeh periodicalsubscribing method based on different preference information. In this paper, 4 types of preference information are discussed , including preference ordering value and utility value giving the orders of alternatives directly, reciprocal judgment matrix and fuzzy complementary judgment matrix obtained by pair comparison between two alternatives indirectly. Firstly, the computing formulas converting the 3 types of preference information, namely, preference ordering, reciprocal judgment matrix and fuzzy complementary judgment matrix, into the forms of utility value are given. Then, a relative entropy aggregation optimal model is proposed from the concept of relative entropy, and the solution to this model is also given. Finally, a case is studied to show the feasibility of this method.