Abstract-

In this paper, we have we have introduced a new intelligent soft-computing method of neutrosophic search with ranks and a new neutrosophic rank sets for neutrosophic relational data model (NRDM). Essentially the data and documents on the Web are heterogeneous; inconsistency is unavoidable in Web mining. Using the presentation and reasoning method of our data model, it is easier to capture imperfect information on the Web which will provide more potentially valued-added information. In Bio-informatics there is a proliferation of data sources. Each research group and each new experimental technique seems to generate yet another source of valuable data. But these data can be incomplete and imprecise, and even inconsistent We could not simply throw away one data in favor of other data. So now we can represent and extract useful information from these data as a challenge. Thus it is a kind of an intelligent search for match in order to answer imprecise queries of the lay users. Our method, being an intelligent soft-computing method, will support the users to make and find the answers to their queries without iteratively refining them by trial and error. This important issue of closeness cannot be addressed with the crisp mathematics. That is why we have used the Neutrosophic tools. Neutrosophic-search method could be easily incorporated in the existing commercial query languages of DBMS to serve the lay users better. So in this Paper Authors are suggesting NRDM and Rank Sets to solve the imprecise query based on Rank Neutrosophic search which is a combination-Neutrosophic Proximity search and a-Neutrosophic-equality Search .

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