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http://dx.doi.org/10.6109/jkiice.2017.21.11.2043

Location Recommendation Customize System Using Opinion Mining  

Choi, Eun-jeong (Department of Computer Science, Sangmyung University)
Kim, Dong-keun (Department of Intelligent Engineering Informations for Human, Sangmyung University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.21, no.11, 2017 , pp. 2043-2051 More about this Journal
Abstract
Lately, In addition to the increased interest in the big data field, there is also a growing interest in application fields through the processing of big data. Opinion Mining is a big data processing technique that is widely used in providing personalized service to users. Based on this, in this paper, textual review of users' places is processed by Opinion mining technique and the sentiment of users was analyzed through k-means clustering. The same numerical value is given to users who have a similar category of sentiment classified as a clustering operation. We propose a method to show recommendation contents to users by predicting preference using collaborative filtering recommendation system with assigned numerical values and marking contents with markers on the map in order of places with high predicted value.
Keywords
Collaborative filtering; Opinion mining; Recommender system; Sentiment analysis;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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