Journal Published Online: 20 July 2022
Volume 51, Issue 3

Data Mining and Analysis Algorithm of Smart City Network Information Resource Description Framework Based on Fuzzy Association Rules

CODEN: JTEVAB

Abstract

Aiming at the problems of poor effect, low precision, and a long time frame in the current data mining analysis algorithm of the network information resource description framework (RDF), a data mining analysis algorithm of the network information RDF based on fuzzy association rules is proposed. Using association rule mining technology combined with fuzzy set theory, a fuzzy association rule algorithm is obtained to deal with quantitative data. Fuzzy c-means (FCM) is used to discretize continuous attributes, and the fuzzy concept pattern and its support and credibility are defined. Add a Mining Query flag to extend the SPARQL Protocol and RDF Query Language (SPARQL) syntax, define the user specified mining model, generate the corresponding project set and transaction, adopt the fuzzy association rule algorithm to generate fuzzy association rules, and realize the RDF data mining analysis of network information. The experimental results show that the network RDF data mining analysis effect of the proposed algorithm is good, which can effectively improve the network RDF data mining analysis accuracy and shorten the mining analysis time.

Author Information

Li, Ruihua
College of Information Engineering, Yulin University, Yulin, Shaanxi Province, China
Feng, Zhidong
College of Information Engineering, Yulin University, Yulin, Shaanxi Province, China
Guo, Hongbo
College of Information Engineering, Yulin University, Yulin, Shaanxi Province, China
Pages: 12
Price: $25.00
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Details
Stock #: JTE20220098
ISSN: 0090-3973
DOI: 10.1520/JTE20220098