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Comparative Studies | Computer Science & Engineering | India | Volume 3 Issue 6, June 2014 | Rating: 7.2 / 10

Comparative Study of Web Content Mining Techniques for HTML and XML Contents

Rupinder Kaur ^[12] | Kamaljit Kaur ^[5]

Abstract: World Wide Web is the rapidly grown source of information. Data on the web is available in many forms which are structured data; unstructured data and semi- structured data. Also it is growing on daily basis. It is becoming difficult to the user to get the relevant data from the web. Data Mining is the subject of computer science which is used to mine useful information from very large amount of data. Web mining is the application of data mining; which implements various techniques of data mining to get the relevant information from the web. Web developers have now started to develop Web pages on emerging Web Technologies like XML; Flash etc. XML was designed to describe data and to focus on what the data is. XML also plays the role of a meta- language and allows authors to create customized markup language for different types of documents; making it a standard data format for online data exchange. To date; famous algorithms like Apriori and FP- Growth algorithms are used to fetch the web data for XML contents and for HTML contents numerous techniques have been proposed. In this paper; a hybrid approach is used to fetch HTML as well as XML contents from a web page. In the hybrid approach; Apriori algorithm is used to remove the unimportant information from the contents and Decision tree is used to fetch the contents from a web page. This hybrid approach is compared with the previous technique implementing FP-Growth algorithm for HTML and XML contents. At the end; results are shown using graphs.

Keywords: Web Mining, XML, Apriori, Decision Tree, FP- Growth algorithm

Edition: Volume 3 Issue 6, June 2014,

Pages: 2099 - 2104