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A recommendation system involving human-in-the-loop to improve the quality of ontologies

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dc.contributor.author Bhattacharyya, Pramit
dc.contributor.author Mutharaju, Vijaya Raghava (Advisor)
dc.date.accessioned 2021-03-26T04:38:04Z
dc.date.available 2021-03-26T04:38:04Z
dc.date.issued 2020-07
dc.identifier.uri http://repository.iiitd.edu.in/xmlui/handle/123456789/864
dc.description.abstract Building an ontology is not only a time-consuming process, but it is also confusing, especially for beginners and the inexperienced. Although ontology developers can take the help of domain experts in building an ontology, they are not readily available in several cases for a variety of reasons. Ontology developers have to grapple with several questions related to the choice of classes, properties, and the axioms that should be included. Apart from this, there are aspects such as modularity and reusability that should be taken care of. From among the thousands of publicly available ontologies and vocabularies such as Linked Open Vocabularies (LOV), it is hard to know the terms (classes and properties) that can be reused in the development of an ontology. A similar problem exists in implementing the right set of ontology design patterns (ODPs) from among the several available. Generally, ontology developers make use of their experience in handling these issues, and the inexperienced ones have a hard time. In order to bridge this gap, we propose a tool named OntoSeer, that monitors the ontology development process and provides suggestions in real-time by interacting with the ontology developers to improve the quality of the ontology under development. It can provide suggestions on the naming conventions to follow, vocabulary to reuse, ODPs to implement, and axioms to be added to the ontology. OntoSeer has been implemented as a Protégé plug-in and is available at github link https://github.com/kracr/ontoseer en_US
dc.language.iso en_US en_US
dc.subject Ontology Engineering, Ontology Quality, Ontology Design Pattern, LOV, and Protégé plug-in en_US
dc.title A recommendation system involving human-in-the-loop to improve the quality of ontologies en_US
dc.type Thesis en_US

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