Web data mining trends and techniques
Ujwala M. Patil, J. B. Patil
Abstract
Ujwala M. Patil, J. B. Patil
Abstract
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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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.
Key concepts: Web mining, Web intelligence, Computer science, Data Web, Web standards, Web mapping, Web modeling, World Wide Web