基于扩展模糊概念网的信息检索结果个性化的研究

Study on Personalizing Results of Information Retrieval Based on Extended Fuzzy Concept Networks

电子文档和用户的增长导致了信息检索结果个性化模式的创新，从而更好地为用户偏好服务。个性化的内容检索旨在改善检索过程中考虑个别用户的特殊兴趣。本文提出了一种基于扩展模糊概念网的信息检索结果的个性化的新方法。在这种方法中，网页和用户偏好都将以扩展模糊概念网形式表示。扩展模糊概念网可看作是关系矩阵和关联矩阵模型，关系矩阵中的元素代表模糊概念间的关系，关联矩阵中的元素表明概念间的关联度。这种方法的好处是能找到用户查询的绝大多数文档并且更灵活、更好地显示给用户。

The increase of electronic documents and their users has led to the creation of new patterns for personalizing results of information retrieval and, which provides better service to users based on their preferences. Personalized content retrieval aims at improving the retrieval process by taking into account the particular interests of individual users. In this paper,we proposes a new method for personalizing results of information retrieval based on extended fuzzy concept networks. In this method, both pages and user profiles will be showed as extended fuzzy concept networks. An extended fuzzy concept network can be modeled by a relation matrix and a relevance matrix, where the elements in a relation matrix represent the fuzzy relationships between concepts, and the elements in a relevance matrix indicate the degrees of relevance between concepts. Advantage of this method is to find the most documents with respect to the user＇s query and more flexible and better showing user.