Formation of categories in document classification systems
Information retrieval systems employ the classification of documents into various categories to facilitate retrieval. The problem of categorization depends on the successful solution to three subproblems: creation of categories, determining the relationship between categories, and maintenance of the categorization system. In existing document categorization systems, the categories are formed by using hit and trial methods. This increases the initial setup period for the system. The initial setup time is further affected by an empirical assignment of relationships between categories.
In this paper, we propose a solution to the problem of developing categories by the application of techniques originating in knowledge acquisition. The approach is based on capturing the knowledge of a user to ensure continuity with the existing categorization system. The use of Personal Construct Theory for knowledge elicitation helps in making explicit the subconscious hierarchical relationships between various categories as perceived by the user.
KeywordsKnowledge Acquisition Information Retrieval System Dependence Tree Repertory Grid Maximum Span Tree
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