원문정보
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
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