Earticle

초록

영어

As the rapid development of integration of informatization and industrialization (IoII), information overload become a serious problem in the knowledge platform for IoII. To address this issue, this paper introduces a hybrid framework based on the assessment system of IoII and user learning behavior. First, using the assessment specification on IoII for industrial enterprises, we establish the similarity model of IoII; then, the similarity model of user behavior is built based on three kinds of learning behaviors in the knowledge platform; at last, after studying the advantages and disadvantages of the two models, this paper proposes a linear fusion framework combining both models. With several experiment conducted, we get the optimal parameters in the framework, and the experimental results show that the proposed framework can achieve the better recommendation quality.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Recommender Algorithm
  3.1. Problem Definition
  3.2. Similarity Model Based on the Assessment of IoII for Industrial Enterprises
  3.3. Similarity Model Based on User Learning  Behavior
  3.4. Neighbor Selection Algorithm and Recommendation Generating
 4. Experimental Analysis
  4.1. Data Sources
  4.2. Performance Evaluation Metrics
  4.3. Results and Discuss
 5. Conclusions
 References

키워드

저자

• Laisong Kang [ School of Economics & Management, Beijing Jiaotong University, Beijing, China ]
• Shifeng Liu [ School of Economics & Management, Beijing Jiaotong University, Beijing, China ]
• Daqing Gong [ School of Economics & Management, Beijing Jiaotong University, Beijing, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605