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Construction of Personalized Recommendation System Based on Back Propagation Neural Network

역전파 신경망을 이용한 개인 맞춤형 상품 추천 시스템 구축

  • 정귀임 (고려대학교 정보경영공학부) ;
  • 박상성 (고려대학교 정보경영공학부) ;
  • 신영근 (고려대학교 정보경영공학부) ;
  • 장동식 (고려대학교 정보경영공학부)
  • Published : 2007.12.28

Abstract

Thousands of studies on predicting information and products that are suitable for customers' preference have been actively proceeding. In massive information, unnecessary information should be removed to satisfy customers' needs. This Information filtering has been proceeding with several methods such as content-based and collaborative filtering etc. These conventional filtering methods have scarcity and scalability problems. Thus, this paper proposes a recommendation system using BPN to solve them. Data obtained by survey questionnaire are used as training data of neural network. The recommendation system using neural network is expected to recommend suitable products because it creates optimal network. Finally, the prototype for recommendation system based on neural network is proposed to collect data and recommend appropriate methods through survey questionnaire. As a result, this research improved the problems of conventional information filtering.

Keywords

ANN(Artificial Neural Network);BPN(Back Propagation Neural Network);Recommendation System;Personalized Service

Cited by

  1. A New QoS-Aware Web Service Recommendation System Based on Contextual Feature Recognition at Server-Side vol.14, pp.2, 2017, https://doi.org/10.1109/TNSM.2017.2693324