Data Mining Techniques for Studying Based on User Home Appliances Behavior in Smart Home

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Transactions on Computer Science and Technology

Transactions on Computer Science and Technology is an international comprehensive professional academic journal of Ivy Publisher, concerning the development of computer science theory and technology application on the combination of computer science and modern industrial technology. The main focus of the journal is the academic papers and comments of latest power electronics theoretical and technical research improvement in the fields of nature s... [More] Transactions on Computer Science and Technology is an international comprehensive professional academic journal of Ivy Publisher, concerning the development of computer science theory and technology application on the combination of computer science and modern industrial technology. The main focus of the journal is the academic papers and comments of latest power electronics theoretical and technical research improvement in the fields of nature science, engineering technology, economy and science, report of latest research result, aiming at providing a good communication platform to transfer, share and discuss the theoretical and technical development of computer science theory and technology development for professionals, scholars and researchers in this field, reflecting the academic front level, promote academic change and foster the rapid expansion of computer science theory and application technology.

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ISSN Print:2327-090X

ISSN Online:2327-0918

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Paper Infomation

Data Mining Techniques for Studying Based on User Home Appliances Behavior in Smart Home

Full Text(PDF, 84KB)

Author: Jianhao ZENG, Wei CHEN

Abstract: The main work of this paper is to use data mining techniques to discover the structure of smart home appliances usage patterns. Particularly, this paper uses home appliances for each hour to be the transaction, and Apriori algorithm, so work out the rule which conform minimum confidence level of 0.6 and minimum support level of 0.2. To adoptive lift to measure the mining patterns, and indicate the patterns are significance, so we can reveal the household appliances usage patterns. This paper provides a new method for the design of smart home system, which can make smart home more intelligent.

Keywords: User Home Appliances Behavior Pattern; Apriori Algorithm; Data Mining

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