Web Page Noise Removal - A Survey

Authors

  • Dr. S. Vijayarani  Assistant Professor, Department of Computer Science, Bharathiar University, Coimbatore, Tamilnadu, India
  • K. Geethanjali  M.Phil Research Scholar, Department of Computer Science, Bharathiar University, Coimbatore, Tamilnadu, India

Keywords:

Web Content, Web page, Global Noise, Local Noise, Filtering.

Abstract

Web mining is used to extract useful information from websites which includes web documents and hyperlinks of web sites. The World Wide Website contains a wide range of web pages which are very useful to many users. Web pages are composed of different kinds of data, such as text, audio, video and images. In addition to this, nowadays, web pages contain a large amount of unnecessary data, e.g., advertisement posters, navigation bars and disclaimer/copyright notices. These types of unnecessary data are called as noisy data. This has created the distractions to the user and also increases the time to perform searches and browsing tasks. To perform in-depth analysis of web data or web content mining, the first and essential step is to remove the noises which are existing in the web pages, and then we can extract useful information from the web pages. Removing noise from the web page is challenging task in web content mining. This main objective of this paper is to discuss the basics of web content mining, types of noises, techniques used for noise removal and different models used in the literature.

References

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International Journal of Scientific Research in Science and Technology

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Published

2017-10-31

Issue

Volume 3, Issue 7, September-October-2017

Section

Research Articles

License

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dr. S. Vijayarani, K. Geethanjali, " Web Page Noise Removal - A Survey, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 3, Issue 7, pp.172-181, September-October-2017.