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Semantic Information and Web based Product Recommendation System – A Novel Approach

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International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 55 - Number 9
Year of Publication: 2012
Authors:
Sneha Y. S
G. Mahadevan
10.5120/8782-2753

Sneha Y.s and G Mahadevan. Article: Semantic Information and Web based Product Recommendation System A Novel Approach. International Journal of Computer Applications 55(9):10-14, October 2012. Full text available. BibTeX

@article{key:article,
	author = {Sneha Y.s and G. Mahadevan},
	title = {Article: Semantic Information and Web based Product Recommendation System  A Novel Approach},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {55},
	number = {9},
	pages = {10-14},
	month = {October},
	note = {Full text available}
}

Abstract

The World Wide Web is today a perennial source of immense information. There is therefore, a definite demand for automated methods that can locate, identify and retrieve information to cater to the individual's requirements, demands or whims. The internet also creates newer possibilities to organize and recommend information. Web usage mining has become popular in various business areas related with Web site development. As the scale of the Internet is getting larger and larger in recent years, we are forced to spend much time to select necessary information from large amount of web pages created. Traditionally In Web usage mining, commonly visited navigational paths are extracted in terms of Web page addresses from the Web server visit logs, and the patterns are used in various applications including recommendation. But semantic information of the Web page contents is generally not included in Web usage mining. The paper has used OWL technology to add semantics to the existing navigational paths. Results shows that our approach fetched better accuracy than the existing web based approach. This paper presents a framework for integrating semantic information along with the navigational patterns. This paper evaluated the framework and it shows promising results in terms of quality recommendation of products.

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