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http://dx.doi.org/10.17661/jkiiect.2018.11.2.181

An Analysis Scheme Design of Customer Spending Pattern using Text Mining  

Jeong, Eun-Hee (Department of Regional Economics, Kangwon National University)
Lee, Byung-Kwan (Department of Software, Catholic Kwandong University)
Publication Information
The Journal of Korea Institute of Information, Electronics, and Communication Technology / v.11, no.2, 2018 , pp. 181-188 More about this Journal
Abstract
In this paper, we propose an analysis scheme of customer spending pattern using text mining. In proposed consumption pattern analysis scheme, first we analyze user's rating similarity using Pearson correlation, second we analyze user's review similarity using TF-IDF cosine similarity, third we analyze the consistency of the rating and review using Sendiwordnet. And we select the nearest neighbors using rating similarity and review similarity, and provide the recommended list that is proper with consumption pattern. The precision of recommended list are 0.79 for the Pearson correlation, 0.73 for the TF-IDF, and 0.82 for the proposed consumption pattern. That is, the proposed consumption pattern analysis scheme can more accurately analyze consumption pattern because it uses both quantitative rating and qualitative reviews of consumers.
Keywords
Collaborative Filtering; Consumption pattern; Cosine similarity; Peason correlation; Text mining; TF-IDF; User review analysis;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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