@article{164,
  author = {S.Sarasvady},
  title = {Meta data-based Text mining for Web Content Categorization},
  journal = {Journal of E-Technology},
  year = {2010},
  volume = {1},
  number = {1},
  doi = {},
  url = {http://www.dline.info/jet/fulltext/v1i1/5.pdf},
  abstract = {In the recent period web resources gain momentum in terms of extensive refined processing resulting the inclusion of a very large number of pages retrieval for any given query. Building taxonomy of the source becomes essential in order to deal with the process of related divisions and terms. The web world has many systems and architectures for processing content-based or context-based features of Source. In this paper we analyze these developments and attempt to generate a set of features to improve web page taxonomy of selected source by classifying web pages as main and fractals. We did a series of testing using an extensive datasets of Source by deploying both using content-based and context-based web page features. Our testing and implementation ensure a high level success in the combination of web content analysis.},
}