A semantic-based ontology mapping - information retrieval for mobile learning resources

摘要

In recent days, Mobile Learning (M-Learning) attains a lot of significance due to its convenience and boundless way of learning. Information retrieval using M-Learning is a challenging and demanding task. For this purpose, some of the techniques are proposed in existing works, but it do not provide the related contents and its results are inaccurate. Moreover, the existing frameworks retrieved many irrelevant information, which leads to high processing time. In order to overcome all these issues, an ontology-based M-Learning framework is introduced in this paper. The main intention of this framework is to reduce the retrieval rate of irrelevant information from the service repository. For this purpose, it performs the mapping and ranking processes with the ontology structure. Moreover, it provides the relevant services to the requested user, which reduces the processing time and computation complexity. This work includes three components such as, user, service user interface and service provider. Initially, the user requests the service to the service provider through the user interface. Then, the service provider receives the request and fetches the related information using the ontology structure. For information retrieval, the processes such as, semantic mapping, sense matching, display relevant information, material ranking and ordered ranking are performed. Moreover, the material repository and clustered repository are utilized to this information. Finally, the service provider fetches the relevant information from these repositories and provides the appropriate service to the requested user. The experimental results evaluate the performance of the proposed system in terms of precision, recall, accuracy, f-measure, term frequency, relevancy, and semantics.