Abstract
Associative search is a key function for extracting information from databases. In this paper, we present a new associative search method with symbolic and semantic operations. This method integrates two kinds of associative search functions. The symbolic associative search is a simple pattern-matching-based function. This function is used as the information filter which repeatedly executes pattern-matching-based comparisons between data items. The semantic associative search function extracts semantically related information by mathematical semantic operations based on the mathematical model of meaning which we have proposed. This function provides a context recognition mechanism for extracting semantically related information from databases. This mechanism makes it possible to put the semantically related data items in order, according to the correlation to the searcher’s impression. The integrated associative search method realizes the advanced information extraction by combining the symbolic and semantic associative search functions.
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Yoshida, N., Kiyoki, Y., Kitagawa, T. (1998). An Associative Search Method Based on Symbolic Filtering and Semantic Ordering for Database Systems. In: Spaccapietra, S., Maryanski, F. (eds) Data Mining and Reverse Engineering. IFIP — The International Federation for Information Processing. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35300-5_6
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DOI: https://doi.org/10.1007/978-0-387-35300-5_6
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