【摘要】 Web数据挖掘是当前数据挖掘的热点研究领域之一,由于Web页面数据的半结构化、不规则性和动态更新等特征,使得基于Web内容的数据挖掘研究具有一定的复杂性.本文首先简介如何从Web页面中提取半结构化数据,接着提出一种增量FP-Growth挖掘方法,使传统的FP-Growth方法适应于动态数据环境的关联规则挖掘,最后以中国汽车市场为例,挖掘消费者对不同类型、不同型号、小同价格轿车的购买偏好.更多还原

【Abstract】 Web-based data mining is a hotspot in the field of Data Mining. For web page’s semi-structure, irregularity and dynamics, it makes web-content based data mining difficult and complex. This paper firstly introduces how to extract semi-structure data from web pages, then provides an approach named incremental FP-Growth, which can apply in dynamic environment for mining the association rules. Finally, as an application in Chinese car market web data, our experiments show the results in car consumption preference in various types, models and prices.更多还原