Please wait a minute...
Computer & Telecommunication  2015, Vol. 1 Issue (9): 60-62    DOI:
Current Issue | Archive | Adv Search |
Research on the Application of Collaborative Filtering Recommendation System Based on Classification
Chen Zebo
Guangzhou Institute of Technology
Download:   PDF(0KB)
Export: BibTeX | EndNote (RIS)      
Abstract  With the development of society, the total amount of library is orders of magnitude increase, people faced a large number of books and literature don’t know how to choice, and the traditional book retrieval technology is not to provide readers with the active and personalized search results. Recommendation system is an intelligent system, it is the user to the target object selection, evaluation of large amounts of information through specific algorithms for processing, according to the processing results in the formation of recommendation list is recommended to the user, in order to provide decision-making reference. This article will study and discuss the collaborative filtering recommendation system based on classification.
Key wordscollaborative filtering      collaborative filtering based on classification      recommendation system     
Published: 09 November 2017
ZTFLH:  TP311.13  

Cite this article:

Chen Zebo. Research on the Application of Collaborative Filtering Recommendation System Based on Classification. Computer & Telecommunication, 2015, 1(9): 60-62.

URL:

http://www.computertelecom.com.cn/EN/     OR     http://www.computertelecom.com.cn/EN/Y2015/V1/I9/60

[1] OU Wei-hong YANG Yong-qin. Research on the Book Recommendation System Based on Mahout under the Big Data Platform[J]. 电脑与电信, 2021, 1(9): 28-31.
[2] SONG Man. A Film Collaborative Filtering Algorithm Based on BP Neural Network[J]. 电脑与电信, 2021, 1(6): 13-18.
[3] GAO Li-qiang MIAO Kai. Improved Collaborative Filtering Recommendation Algorithm of Online Courses [J]. 电脑与电信, 2021, 1(6): 53-56.
[4] SONG Man. ACollaborative Filtering RecommendationAlgorithm Based on User Preference[J]. 电脑与电信, 2020, 1(12): 17-21.
[5] GENG Yi-wen. Research on Recommendation System Based on StackedAutoencoder[J]. 电脑与电信, 2020, 1(11): 65-70.
[6] YANG Yao-ke. An Improve Collaborative Filtering Recommendation Algorithm Based on Item Similarity Measurement[J]. 电脑与电信, 2018, 1(12): 23-.
[7] LV Hai-yan. Research on the Recommendation System of Motorcycle Logistics Scale Control Based on User Behaviors-A Case for Motorcycle Logistics in Pearl River Delta of China [J]. 电脑与电信, 2018, 1(11): 18-21.
[8] TAO Yi. Research on Resource Push Service and Key Strategy Based on E-learning[J]. 电脑与电信, 2017, 1(11): 12-13.
[9] Wang Yulin, Wang Yongjian, Chai Zhengyi. Personalized Recommendation System Based on Immune Algorithm[J]. 电脑与电信, 2016, 1(10): 1-3.
[10] Chen Hang. Design of Tag Recommendation System Based on Hadoop[J]. 电脑与电信, 2015, 1(7): 59-61.
[11] Lu Xiaoya Song Qiuli. Research of Collaborative Filtering Technology Based on the Change of User Interest[J]. , 2012, 1(3): 0-0.
Copyright © Computer & Telecommunication, All Rights Reserved.
Powered by Beijing Magtech Co. Ltd