基于模糊值概念网的模糊信息检索研究

在模糊值概念网中，任意两概念间的关联度可用模糊数的任意形式表示，概念间的关系可为模糊正相协或模糊负相协。为了减少模糊推理时间，模糊值概念网可看作是由关联矩阵和关系矩阵组成，关联矩阵中的元素代表概念问的关联度．关系矩阵中的元素代表概念间的关系。使用模糊正相协和模糊负相协可准确地表示用户的查询，增强了模糊信息检索系统的灵活性。将模糊值概念网的结构扩展到互联网，提出了一种基于网络型的模糊值概念网的模糊信息检索方法，在分布式网络中能进行相对较为有效的信息检索。

Fuzzy information retrieval based on fuzzy-valued concept networks

The relevant degree between any two concepts in a fuzzy-valued concept network can be represented by arbitrary shapes of fuzzy numbers,and the relationship between two concepts might be a fuzzy positive or negative association.In order to reduce the time of fuzzy inference,the fuzzy-valued concept networks can be seen composed of the relevant matrices and the relationship matrices.The elements of a relevant matrix represent the relevant degrees between concepts,while the elements of a relationship matrix represent the relevant relationships between concepts.The use of the fuzzy positive and negative association relationship can formulate users’ queries correctly and increase the flexibility of fuzzy information retrieval systems.Expanding the fuzzy-valued concept networks to the Internet environment,we propose a fuzzy information retrieval method based on the Internet fuzzy-valued concept network.Information retrieval can be effectively done in the distributed network.