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http://dx.doi.org/10.9717/kmms.2017.20.7.1065

A Method for Short Text Classification using SNS Feature Information based on Markov Logic Networks  

Lee, Eunji (Dept. of Computer Engineering, Chosun University)
Kim, Pankoo (Dept. of Computer Engineering, Chosun University)
Publication Information
Journal of Korea Multimedia Society / v.20, no.7, 2017 , pp. 1065-1072 More about this Journal
Abstract
As smart devices and social network services (SNSs) become increasingly pervasive, individuals produce large amounts of data in real time. Accordingly, studies on unstructured data analysis are actively being conducted to solve the resultant problem of information overload and to facilitate effective data processing. Many such studies are conducted for filtering inappropriate information. In this paper, a feature-weighting method considering SNS-message features is proposed for the classification of short text messages generated on SNSs, using Markov logic networks for category inference. The performance of the proposed method is verified through a comparison with an existing frequency-based classification methods.
Keywords
Short Text Classification; Markov Logic Networks; Feature Weighting;
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Times Cited By KSCI : 1  (Citation Analysis)
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