KNOWLEDGE-BASED CLUSTERING SCHEME FOR COLLECTION MANAGEMENT AND RETRIEVAL OF LIBRARY BOOKS
We propose a knowledge-based clustering scheme for grouping books in a library. Such a grouping is achieved with the help of domain knowledge in the form of the ACM CR (Computing Reviews) category hierarchy. A new knowledge-based similarity measure is defined and used in clustering books. The proposed scheme is useful in overcoming several problems associated with the existing book collection management and document retrieval systems. More specifically, it can be used in: (1) helping the user select an appropriate collection of books in a library which contains the topics of interest; (2) assigning a classification number to a new book; (3) designing a more appropriate and uniform classification scheme for books; and (4) comparison of libraries based on their collections. Initial experiments on a collection of hundred books using the proposed clustering scheme have given us encouraging results.
knowledge-based clustering collection management library books domain knowledge similarity measure document retrieval