Enhancement of TOPSIS for Evaluating the Web-Sources to Select as External Source for Web-Warehousing

In this paper, the main concern is to evaluate the web-sources, which are to be selected as an external source for web-warehousing. In order to identify the web sources, they are evaluated on the basis of their multiple features. For it, Multi-Criteria Decision Making (MCDM) approach is used. In this paper, among all the MCDM approach, the focus is on “Technique for Order Preference by Similarity to Ideal Solution” (TOPSIS) approach and proposing an enhancement in this method. The traditional TOPSIS approach uses Euclidean Distance to measure the similarity. Here, Jeffrey Divergence has been proposed instead of Euclidean Distance to compute the similarity measure which includes asymmetric and symmetric distances during computation. Experimental analysis of both the variations of TOPSIS approach have been conducted and the result shows the enhancement in the selection of web sources.