2002Unpublished venueRequires access

Indexing fuzzy data

Sven Helmer

Open publisher page 4 citations

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.

About this research paper

What this paper is about

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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OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available 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.

Key concepts: Computer science, Search engine indexing, Inverted index, Data mining, Information retrieval, Coding (social sciences), Fuzzy logic, Database index

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