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Implementing E-Learning Ontology to Scale for Provenance
Author(s) -
Amit Kumar Bajpai,
Rajiv Pandey,
S P Tripathi
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i7735.078919
Subject(s) - computer science , ontology , cloud computing , world wide web , semantic web , information retrieval , rendering (computer graphics) , structuring , data science , artificial intelligence , philosophy , epistemology , finance , economics , operating system
This paper explores the aspects of providing education through E-learning model evaluating its relevance to distance education and for ICT systems. A subset of E-learning is a Web based learning that makes the learning -easier, impressive, structured and properly managed. The paper defines an university ontology describing how e-learning provides resources which are available online and designated cloud that can be delivered anywhere any time among the users. In the proposed model data is stored in designated cloud and users are able to share efficiently the same as it provides services to learner. Provenance or trust with respect to the academic resource is a major concern in these types of models, users accessing data must be trustable which help learners, researchers, developers, and users in future work also. This paper proposes an e-learning model which is well organized and structured, such that the machine responds with the accurate, trustable, desired information and results. The paper defines an ontology for semantic structuring, semantic rendering and applies provenance on suggested ontology to achieve authentic results. It is also desired to establish trust of the source contents of the Semantic Web, with the result that a user receiving data will need to verify whether the received data from source is in fact trustable or not. The defined ontogoly is suitable for consumption of both man and machine in the context of the e-learning and Semantic data rendering Web Keywords

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