A concept space approach to semantic exchange

This dissertation work investigates the use of information technologies that clarify semantic meaning to help users elaborate their information needs by providing library-specific knowledge to the information seeking process. The research involved two interdependent semantic technologies: concept space consultation and library-specific, domain-specific, automatically generated concept spaces. The concept space consultation phase used spreading activation algorithms—branch-and-bound and Hopfield net algorithms—to explore knowledge sources in specific domains. This research demonstrated the comparable effectiveness of exploration of a library database using a man-made classification scheme and thesaurus as opposed to an automatically generated concept space. The results showed that the use of spreading activation algorithms identified more relevant concepts than the use of the manual browsing method. The concept space technique automatically identifies and extracts concept from a library collection while at the same time computing the strength of associations between concepts. This research demonstrated that the concept space technique was able to create human-recognizable concepts and their associations. In addition, the technique could be scaled to generate very large library-specific concept spaces for a very large underlying library collection. Moreover, the interdependent use of both semantic technologies creates a semantic medium for users and library-specific knowledge sources to exchange content with context—context in user information need and that in corporeal knowledge.

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