Representation and handling of inexactness in information has become the major issues in modern database system and next generation information systems. In order to deal with the information inexactness, fuzzy logic is integrated with various database model and theories. This paper presents a query processing model could coupled with fuzzy logic in XML database system. Our system is based on traditional XML databases, while permitting the storage of fuzzy data as well as crisp data. Crisp data are the usual precise data handled by the traditional databases whereas fuzzy logic gives the output in certain range. In this paper we are dealing with the concept of critical architectural component named fuzzy meta-knowledge base. The main aim of fuzzy meta-knowledge basis to keep the different types of fuzzy divisions for database attributes. Fuzzy meta-knowledge base defines and demonstrates data of fuzzy nature is stored in the fuzzy meta-knowledge base. The fuzzy query language is based on X-PATH. It can accept any type of fuzzy expressions in any condition in query part. For improving the performance of X-PATH, we are using Parallel Path Stack algorithm. Parallel Path Stack algorithm speed XML Query processing performance significantly.
In this paper, we p ropose a proficient method for knowledge management in Edaphology to assist the edaphologists and those related with agricu lture in a big way. The proposed method mainly consists two sections of wh ich the first one is to build the knowledge base using XML and the latter part deals with informat ion retrieval by searching using fuzzy. Initially, the relational database is converted to the XML database. The paper discusses two algorith ms, one is when the soil characteristics are inputted to have the plant list and in the other, plant names are inputted to have the soil characteristics suited for the plant. While retrieving the query result, the crisp numerical values are converted to fuzzy using the triangular fu zzy membership function and matched to those in database. And those which satisfy are added to the result list and subsequently the frequency is found out to rank the result list so as to obtain the final sorted list. Performance metrics used in order to evaluate the method and compare it to baseline paper are nu mber of plants retrieved, ranking efficiency, and computation time and memory usage. Results obtained proved the validity of the method and the method obtained average computation time of 0.102 seconds and average memory usage of 2486 Kb , which all are far better than the previous method results.
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