This paper presents a user-based approach to exploring the possibility of adding user-oriented class associations to hierarchical library classification schemes. Some highly associated classes not grouped in the same subject hierarchies, yet are relevant to users' knowledge are automatically obtained by analyzing a two-year log of book circulation records from a university library. The approach employs methods from both collaborative filtering and information retrieval research to discover associated classes based on the circulation patterns of similar users. The experimental results show that classification schemes can be, therefore, made more adaptable to changes of users and the uses of different library collections. The implications for applications in information organization and retrieval are also discussed.
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