User interest mining on Sina Weibo is the basis of personalized recommendations,advertising,marketing promotions,and other tasks.Although great progress has been made in this area,previous studies have ignored the dif...User interest mining on Sina Weibo is the basis of personalized recommendations,advertising,marketing promotions,and other tasks.Although great progress has been made in this area,previous studies have ignored the differences among users:the varied behaviors and habits that lead to unique user data characteristics.It is unreasonable to use a single strategy to mine interests from such varied user data.Therefore,this paper proposes an adaptive model for user interest mining based on a multi-agent system whose input includes self-descriptive user data,microblogs and correlations.This method has the ability to select the appropriate strategy based on each user’s data characteristics.The experimental results show that the proposed method performs better than the baselines.展开更多
In the advance of E-commerce, the importance of predicting the next request of a user as he or she visits Web pages grows larger than before. Web usage mining is the process of applying data mining to the discovery of...In the advance of E-commerce, the importance of predicting the next request of a user as he or she visits Web pages grows larger than before. Web usage mining is the process of applying data mining to the discovery of user behavior patterns based on Web log data, well suited to this problem. As an important field of Web usage mining, mining user navigation patterns is the fundamental approach for generating recommendations. In this paper, we propose an ant colony approach for navigation patterns. We use the ant theory as a metaphor to guide user＇s choice in the Web site.展开更多
文摘User interest mining on Sina Weibo is the basis of personalized recommendations,advertising,marketing promotions,and other tasks.Although great progress has been made in this area,previous studies have ignored the differences among users:the varied behaviors and habits that lead to unique user data characteristics.It is unreasonable to use a single strategy to mine interests from such varied user data.Therefore,this paper proposes an adaptive model for user interest mining based on a multi-agent system whose input includes self-descriptive user data,microblogs and correlations.This method has the ability to select the appropriate strategy based on each user’s data characteristics.The experimental results show that the proposed method performs better than the baselines.
基金This research is supported by National Natural Science Foundation of China （70471046）, and Doctoral Fund of State Education Ministry（20040359010）.
文摘In the advance of E-commerce, the importance of predicting the next request of a user as he or she visits Web pages grows larger than before. Web usage mining is the process of applying data mining to the discovery of user behavior patterns based on Web log data, well suited to this problem. As an important field of Web usage mining, mining user navigation patterns is the fundamental approach for generating recommendations. In this paper, we propose an ant colony approach for navigation patterns. We use the ant theory as a metaphor to guide user＇s choice in the Web site.
