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http://dx.doi.org/10.5392/JKCA.2012.12.04.076

Study on Designing and Implementing Online Customer Analysis System based on Relational and Multi-dimensional Model  

Kim, Keun-Hyung (제주대학교 경영정보학과)
Song, Wang-Chul (제주대학교 컴퓨터공학과)
Publication Information
The Journal of the Korea Contents Association / v.12, no.4, 2012 , pp. 76-85 More about this Journal
Abstract
Through opinion mining, we can analyze the degree of positive or negative sentiments that customers feel about important entities or attributes in online customer reviews. But, the limit of the opinion mining techniques is to provide only simple functions in analyzing the reviews. In this paper, we proposed novel techniques that can analyze the online customer reviews multi-dimensionally. The novel technique is to modify the existing OLAP techniques so that they can be applied to text data. The novel technique, that is, multi-dimensional analytic model consists of noun, adjective and document axes which are converted into four relational tables in relational database. The multi-dimensional analysis model would be new framework which can converge the existing opinion mining, information summarization and clustering algorithms. In this paper, we implemented the multi-dimensional analysis model and algorithms. we recognized that the system would enable us to analyze the online customer reviews more complexly.
Keywords
Multi-dimensional Analysis Model; Opinion Mining; Information Summarization; Clustering; Association Rules Mining; Relational Model;
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Times Cited By KSCI : 1  (Citation Analysis)
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