Knowledge-based clustering scheme for collection management and retrieval of library books

作者:

Highlights:

摘要

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.

论文关键词:Knowledge-based clustering,Similarity measure,Document retrieval,Library books,Collection management,Domain knowledge

论文评审过程:Received 3 June 1994, Revised 23 November 1994, Accepted 3 January 1995, Available online 7 June 2001.

论文官网地址:https://doi.org/10.1016/0031-3203(94)00173-J