基于喜好标签的移动互联网用户行为分类研究

摘要

提出一种基于移动互联网个体用户的实际行为得出其喜好标签，据此将同类信息推送给个体用户的方法，该方法能够实现精确推送，因此推送的内容更加容易被用户接受，从而商业价值性价比更高。首先阐述了个体用户实际行为数据的提取方法，比较了各方法的优缺点；其次提出了一种固定质心的k-means文本聚类方法，能够快速、准确地实现用户喜好标签分类；最后分析了精确营销模式以及后续的研究方向。%This paper presented a method that drew the preference tag of mobile internet user based on their actual behavior data and delivered the same kind of information to them by the classification result. The method made precise delivering, so the content was more easily accepted by the user, thus the commercial value was higher. Firstly, this paper introduced extraction methods of individual user’s actual behavior data with each method’s advantages and disadvantages compared. Secondly, it proposed a ifxed centroids k-means clustering method that could implement the classiifcation of preference tag quickly and accurately. Finally, it analyzed the precision marketing model and the direction for further research.