An increasing number of ontology extraction based on domain knowledge are adopted in E-learning. It is critical that domain ontologies cannot sufficiently handle imprecise and vague knowledge, but fuzzy ontology can effectively resolve data with uncertainty. This paper proposes novel fuzzy domain ontology acquisition algorithm for E-Learning application. The knowledge construction mechanism constructs fuzzy concept and relation based on concepts. We have then proposed our design for extracting concepts from heterogeneous text documents.

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Grid Computing is intended to provide resource sharing and solve huge amount of complicated problems. In Multicluster Systems, jobs may require co-allocation, that is, the simultaneous allocation of resources such as processors in multiple clusters. Such jobs may have low runtimes because they access more number of resources. In processor coallocation, advanced processor reservation is needed. But this becomes one of the challenges in processor co-allocation. Advanced Processor Reservation Algorithm based on the priority of jobs using the usage of memory is implemented in this paper. The results indicate that the overall performance of the algorithm is increased by satisfying large number of reservation requests using the priority.

Approximate Membership Localization (AML) is concerned with locating non-overlapped substrings thus avoiding redundancies. This overcomes the drawback of Approximate Membership Extraction (AME) process which has low efficiency for real world application. An algorithm called P-Prune is used in Blog search. This prunes most of the overlapped redundant substrings before generating them. Here we use the opinion retrieval scheme which analyses the viewers' comments on Blog contents. Our experimental study on blogs reveals the efficiency of P-Prune over AME method. We also work AML in application to a proposed Blog search framework, a search-based approach joining two tables using dictionary-based entity recognition from blogs. Apart from the advantage of AML over AME, the experiment also proves the efficiency of the search-based approach. This algorithm can be extended to video blogs (vlog) also.