Paper Title:
Research on Applying User-Based Collaborative Filtering Algorithms to Building Products Selection
  Abstract

Nowadays, there are lots of internet-based service platforms about construction products. The building products’ types are too many to select. This paper proposes an algorithm applying user-based collaborative filtering method to building products selection, which implements personalized recommendation with the help of group users’ experience. The algorithm provides decision support to relevant personnel and improves the efficiency and quality of building products selection.

  Info
Periodical
Chapter
Chapter 5: Monitoring and Control of the Manufacturing Process
Edited by
Zhijiu Ai, Xiaodong Zhang, Yun-Hae Kim and Prasad Yarlagadda
Pages
396-399
DOI
10.4028/www.scientific.net/AMR.339.396
Citation
L. M. Sun, F. J. Luan, T. B. Liu, "Research on Applying User-Based Collaborative Filtering Algorithms to Building Products Selection", Advanced Materials Research, Vol. 339, pp. 396-399, 2011
Online since
September 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Zhong Ping Zhang, Yong Xin Liang
Abstract:This paper proposes a new data stream outlier detection algorithm SODRNN based on reverse nearest neighbors. We deal with the sliding window...
1032
Authors: Dong Wang, Shi Huan Xiong
Chapter 8: Nanomaterials and Nanomanufacturing
Abstract:The learning sequence is an important factor of affecting the study effect about incremental Bayesian classifier. Reasonable learning...
1455
Authors: Li Hua Wu, Wen Feng Chen
Chapter 6: Information Technologies, WEB and Networks Engineering, Information Security, Software Application and Development
Abstract:Collaborative filtering recommendation is a mainstream personalized recommendation method, which has some flaws in actual application. And...
2288
Authors: Pei Ye, Tao Jiang
Chapter 4: Practice of Data Processing for Intelligent Systems
Abstract:In this paper, the recognition system of fuzzy clustering based on BP feature screening was put out. The figure specimens of experiment were...
504
Authors: Ping Wu, Tao Yu, J.B. Du, G.Q. Qu, Feng Xiong
Chapter 5: Information Technology and Computer Science, Networks
Abstract:In order to meet the increasing personalized needs of users in the steel trading platform, the intelligent recommendation system has been...
687