Earticle

초록

영어

With the rapid development of information technology and the Internet, people entered the era of information overload. Recommended system is an effective tool to solve the problem of information overload, it is based on the historical behavior of users and other records of interest to the user modeling, and then use the model to create user interest personalized recommendation, the interested user information, products. Online Intelligence is a new research direction, which integrates the latest achievements of artificial intelligence and information technology, greatly emphasizes on the Internet means intelligent application of data mining technology in the online intelligence research has a very important position. This paper presents a project-based collaborative filtering algorithm hierarchical similarity. Users to take advantage of some of the projects marked tags and project categories were automatically extended, to establish a hierarchy of all projects, and then use similar items tag hierarchy established between computing projects. Experimental results show that compared with traditional collaborative filtering algorithm, the ability of collaborative filtering algorithm based on similarity of item level can significantly improve the recommendation system to handle large data presented in this paper.

목차

Abstract
 1. Introduction
 2. Research Status and Related Theory
  2.1. Data Mining and Online Intelligence Technology
  2.2. The Main Technical Methods of Data Mining
  2.3. Recommended System Concept
 3. Intelligent Recommendation System
  3.1. E-Commerce Development and Demand
  3.2. Content-Based Recommendation
  3.3. Collaborative Filtering Recommendation
 4. Experiment and Analysis
  4.1. System Design
  4.2. Forecast Accuracy
 5. Conclusions
 Acknowledgments
 References

키워드

저자

• Yongfeng Cui [ School of Science and Technology, Zhoukou Normal University, Zhoukou Henan 466001, China ]
• Yuankun Ma [ School of Science and Technology, Zhoukou Normal University, Zhoukou Henan 466001, China ]
• Zhongyuan Zhao [ College of Information Science and Engineering, Henan University of Technology, Zhengzhou, Henan 450001, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605