Earticle

초록

영어

A recommendation system that predicts customer preferences and recommends products to users is used in various fields. Most recommendation systems often use an overall evaluation of a rating or review, and if only an overall evaluation of a review is used, there is a limit to reflecting the detailed attributes of the review data. Therefore, this study builds a customer-attribute matrix by emotionally analyzing reviews left by customers by attribute. We then use optimization techniques to calculate the weights of each matrix and combine them into one matrix to propose a model that utilizes the results of extracting customer-to-customer similarities for collaborative filtering.

목차

Abstract
Introduction
Methods
Evaluation
References

저자

• 이유린 [ 국민대학교 비즈니스IT전문대학원 ]
• 박종현 [ 국민대학교 비즈니스IT전문대학원 ]
• 안현철 [ 국민대학교 비즈니스IT전문대학원 ]

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