Web数据挖掘的趋势和技术

U. Patil, J. Patil
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引用次数: 11

摘要

Web服务和基于Web的应用程序正以指数级的速度增长。这产生了大量具有自己独特特征的Web数据。这反过来又使Web数据挖掘领域的研究更具挑战性。Web数据挖掘是数据挖掘的一种应用,它处理从万维网中提取有趣的或隐藏的知识。Web数据挖掘可以分为:Web内容挖掘、Web结构挖掘和Web使用挖掘。在本文中,我们调查了这三种类型的Web数据挖掘的最新技术,从而描述了各种特定的趋势和技术。我们还讨论了与Web数据挖掘研究相关的不同挑战和问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Web data mining trends and techniques
Web Services and Web-based applications are growing at an exponential rate. This is generating a huge amount of Web data having its own peculiar characteristics. This in turn makes research in the area of Web Data Mining more challenging. Web Data Mining is an application of Data Mining which deals with extraction of interesting or hidden knowledge from the World Wide Web. Web Data Mining can be categorized into: Web Content Mining, Web Structure Mining, and Web Usage Mining. In this paper, we survey the state-of-the-art in each of these three types of Web Data Mining thereby describing a variety of specific trends and techniques. We also discuss different challenges and issues pertaining to Web Data Mining research.
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