Since collaborative filtering (CF) based recommendation methods rely on neighbors as information sources, their performance depends on the quality of neighbor selection process. However, conventional CF has a few fund...
详细信息
ISBN:
(纸本)9783540788485
Since collaborative filtering (CF) based recommendation methods rely on neighbors as information sources, their performance depends on the quality of neighbor selection process. However, conventional CF has a few fundamental limitations that make them unsuitable for web content services: recommender reliability problem and no consideration of customers' heterogeneous susceptibility on information sources. To overcome these problems, we propose a new CF method based on the source credibility model in consumer psychology. the proposed method extracts each target customer's part-worth on source credibility attributes using conjoint analysis. the results of the experiment using the real web usage data verified that the proposed method outperforms the conventional methods in the personalized web content recommendation.
An essential problem of automatic web service planning is, how to compose the services together with minimal human effort. Most composition mechanism depends on relevant feedback method to ask the user to change the r...
详细信息
the aim of this study was to examine the effectiveness of a study support system introduced into a class of the first grade (7 years old) of a Japanese elementary school to support children in reporting activities to ...
详细信息
暂无评论