Semantic based for E-Learning content storage on cloud

E-Learning represents an innovative shift in the field of learning, providing rapid access to specific knowledge and information. It offers online content that can be delivered anytime and anywhere through a wide range of electronic learning solution. Storage as a service model of the cloud helps to store e-content materials in distributed environment so that it can be accessed efficiently. Here, a novel model is proposed for semantic based content storing of E-Learning materials on the cloud. e-content here refers to collection of text, audio and video clippings. Text documents alone are separated out. LDA (Latent Dirichilet Algorithm) technique is applied, to extract the topical keywords from the learning objects. The e-content materials, including text materials are segmented into learning objects. Each learning object is represented as a mixture of topics, and is associated with a probability distribution representing importance of the topic for that e-content. The extracted topics are matched with the domain taxonomy to get their corresponding topic levels. Finally Metadata is created based on the semantics of the e-content and is stored in the repository. This metadata which is stored on the cloud act as a semantic metadata and helps in effective retrieval of e-content materials. The performance of semantic based e-content storage on the cloud is compared with primitive methods and is proved to be effective.