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Abstract
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Article Information:
Efficient Clustering of Web Search Results Using Enhanced Lingo Algorithm
M. Manikantan and S. Duraisamy
Corresponding Author: M. Manikantan
Submitted: September 18, 2014
Accepted: October 01, 2014
Published: February 15, 2015 |
Abstract:
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Web query optimization is the focus of recent research and development efforts. To fetch the required information, the users are using search engines and sometimes through the website interfaces. One approach is search engine optimization which is used by the website developers to popularize their website through the search engine results. Clustering is a main task of explorative data mining process and a common technique for grouping the web search results into a different category based on the specific web contents. A clustering search engine called Lingo used only snippets to cluster the documents. Though this method takes less time to cluster the documents, it could not be able to produce the clusters of good quality. This study focuses on clustering all documents using by applying semantic similarity between words and then by applying modified lingo algorithm in less time and produce good quality.
Key words: Clustering algorithm, lingo algorithm, search engine optimization, semantic web, snippet, web query optimization,
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Cite this Reference:
M. Manikantan and S. Duraisamy, . Efficient Clustering of Web Search Results Using Enhanced Lingo Algorithm. Research Journal of Applied Sciences, Engineering and Technology, (5): 359-364.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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