SERVICE AND FREQUENT MEASURE FOR E-LEARNING THROUGH CLOUD COMPUTING USING MOSCSM

Abstract

The E-Learning (EL) is the process of learning any subject or gathering any information through the web and there are many educational institutions enforced EL concepts, so that the students of the university could be able to learn through the web registration. The growth of cloud computing (CC) has been identified as an optimal platform, where the resources can be deployed and accessed through internet by the external world. This paper proposed to improve the Multimedia Objective Sentence Case Similarity Measure (MOSCSM) for efficient Distance Learning (DL) on cloud environment using information similarity Measure. In this approach, selection of service has been performed in another dimension. However, there exist number of services available for any subject of EL scenario; the relation of information returned by the service for any topical query has to be measured. Knowledge learning process points to the relational service based on the user service selection. Each service would produce different results for the same query from the learner. It is necessary to measure the information similarity measure which represents the relatedness or relevancy of the query and result produced. Such approach would improve the performance of service selection in the DL of cloud systems.