基于模糊关联规则的微博用户潜在兴趣发现

针对微博用户兴趣随时间变化的特征,提出一种基于模糊关联规则的潜在兴趣发现方法(PIDFAR),利用LDA主题模型表达微博主题分布,通过时间加权的方式计算出用户现在兴趣的主题分布,进行模糊关联规则挖掘,得出关联规则集合以表示和发现用户兴趣随时间发生变化的一般规律,最后根据关联规则集合中关联规则和用户现在兴趣的主题分布来计算相似度,取相似度较高的关联规则的后项的集合组成用户的潜在兴趣.实验表明, PIDFAR方法能够使得用户潜在兴趣的发现过程脱离用户的好友群体限制,相比基于协同过滤技术的潜在兴趣发现方法明显提高了发现微博用户潜在兴趣的准确率.

Discovering Micro-Blog User's Potential Interests Based on Fuzzy Association Rules

According to the specific characteristic of the micro-blog user's interests changing with time, a potential interest discovery method based on fuzzy association rules(PIDFAR) is proposed. It could express micro-blog theme distribution by using LDA topic model, and then use the time weighted method to calculate user's recent interest subject distribution, for mining fuzzy associate rules. That set of association rules to express and discover the general rule of user's interests change over time. Finally, after calculating the similarity between the the associated rule of association rule in the collection and the topic distribution of user's interest, take the high similarity of the latter collection in association rules set to constitute the user's potential interests. Experiments show that the method of PIDFAR can make the process of discover the user's potential interest break away from the limit of user's friends group, and improve the accuracy of the discovery of potential interests of micro-blog users obviously than the traditional method of discovery potential interest based on collaborative filtering technology.