A Novel Approach for Clustering of Heterogeneous Xml and HTML Data Using K-means

Abstract

Data mining is a phenomenon of extraction of knowledgeable information from large sets of data. Now a day’s data will not found to be structured. However, there are different formats to store data either online or offline. So it added two other categories for types of data excluding structured which is semi structured and unstructured. Semi structured data includes XML etc. and unstructured data includes HTML and email, audio, video and web pages etc. In this paper data mining of heterogeneous data over Xml and HTML, implementation is based on extraction of data from text file and web pages by using the popular data mining techniques and final result will be after sentimental analysis of text, semi-structured documents that is XML files and unstructured data extraction of web page with HTML code, there will be an extraction of structure/semantic of code alone and also both structure and content.. Implementation of this paper is done using R is a programming language on Rstudio environment which commonly used in statistical computing, data analytics and scientific research. It is one of the most popular languages used by statisticians, data analysts, researchers and marketers to retrieve, clean, analyze, visualize, and present data.