Improving Efficiency of Textual Static Web Content Mining Using Clustering Techniques

There are several efficient methods for the discovery or mining of various types of data, methods devised for mining textual static web content have always been proved less efficient due to the data's ambiguous, unclassified, unstructured or unclustered nature. Various association rule mining algorithms like Generalized pattern algorithm are being implemented to mine the web content but again due to the above setbacks the efficiency expected from the algorithm is not obtained. Since the dip in the efficiency of these algorithms is amounted to the nature of the textual web content, an algorithm which may deal with, if not all the anomalies at least the unclustered nature of the content may increase the efficiency drastically.
Provided by: Journal of Theoretical and Applied Information Technology Topic: Developer Date Added: Nov 2011 Format: PDF

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