Indexing fuzzy data
Sven Helmer
Abstract
Sven Helmer
Abstract
Providing efficient query processing in database systems is one step in gaining acceptance of such systems by end users. We propose several techniques for indexing fuzzy sets in databases to improve the query evaluation performance. Three of the presented access methods are based on superimposed coding, while the fourth relies on inverted files. The efficiency of these techniques was evaluated experimentally. We present results from these experiments, which clearly show the superiority of the inverted files.
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Providing efficient query processing in database systems is one step in gaining acceptance of such systems by end users. We propose several techniques for indexing fuzzy sets in databases to improve the query evaluation performance. Three of the presented access methods are based on superimposed coding, while the fourth relies on inverted files. The efficiency of these techniques was evaluated experimentally. We present results from these experiments, which clearly show the superiority of the inverted files.
Key concepts: Computer science, Search engine indexing, Inverted index, Data mining, Information retrieval, Coding (social sciences), Fuzzy logic, Database index