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http://dx.doi.org/10.13088/jiis.2022.28.2.001

An Intelligent Recommendation System by Integrating the Attributes of Product and Customer in the Movie Reviews  

Hong, Taeho (College of Business Administration, Pusan National University)
Hong, Junwoo (College of Business Administration, Pusan National University)
Kim, Eunmi (Kookmin Information Technology Research Institute, Kookmin University)
Kim, Minsu (College of Business Administration, Pusan National University)
Publication Information
Journal of Intelligence and Information Systems / v.28, no.2, 2022 , pp. 1-18 More about this Journal
Abstract
As digital technology converges into the e-commerce market across industries, online transactions have activated, and the use of online has increased. With the recent spread of infectious diseases such as COVID-19, this market flow is accelerating, and various product information can be provided to customers online. Providing a variety of information provides customers with various opportunities but causes difficulties in decision-making. The recommendation system can help customers to make a decision more effectively. However, the previous research on recommendation systems is limited to only quantitative data and does not reflect detailed factors of products and customers. In this study, we propose an intelligent recommendation system that quantifies the attributes of products and customers by applying text mining techniques to qualitative data based on online reviews and integrates the existing objective indicators of total star rating, sentiment, and emotion. The proposed integrated recommendation model showed superior performance to the overall rating-oriented recommendation model. It expects the new business value to be created through the recommendation result reflecting detailed factors of products and customers.
Keywords
Recommendation system; Collaborative filtering; SVD; Text mining; Movie review;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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