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The process of developing a data warehouse starts with identifying and gathering requirements, designing the dimensional model followed by testing and maintenance. The design phase is the most important activity in the successful building of a data warehouse. In this paper, we surveyed and evaluated the literature related to the various data warehouse design approaches on the basis of design criteria and propose a generalized object oriented conceptual design framework based on UML that meets all types of user needs.

This research proposes a novel lexical approach to text categorization in the bio-medical domain. We have proposed LKNN (Lexical KNN) algorithm, in which lexemes (tokens) are used to represent the medical documents. These tokens are used to classify the abstracts by matching them with the standard list of keywords specified as MESH (Medical Subject Headings). It automatically classifies journal articles of medical domain into specific categories. We have used the collection of medical documents, called Ohsumed, as the test data for evaluating the proposed approach. The results show that LKNN outperforms the traditional KNN algorithm in terms of standard F-measure.

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