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Akinwumi, Hannah and Covenant University, Theses (2021) DEVELOPMENT OF A KNOWLEDGE GRAPH MODEL FOR RESOURCE MANAGEMENT IN E-LIBRARY. Masters thesis, Covenant University Ota..

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Electronic libraries grant communities access to electronic resources, aiding information seekers to acquire knowledge and utilize them for various purposes. The ambiguity of the natural language that makes it difficult to get a perfect match between a user’s query and resources or document is an inherent challenge to any information retrieval system that deals with text. Techniques from information visualization like knowledge graph will be valuable to describe collections can optimize information retrieval services in several aspects such as recommendation and reference services. Some library users do not know how to search for the resources and materials they need. Some other categories of users come with only ideas to the library looking for resources. There are also case where librarians have to sources for materials to archive at the reference section of the library. This study provided a knowledge graph model of resources in E-library, boosted the information search and facilitated information retrieval more efficiently. This study collected dataset from an academic database and preprocessed after which the dataset was Transformed to Java Script Object Notation (JSON). The Resource Description Framework (RDF) modeled the data using turtle syntax to generate the schema. Entity and relationship was extracted with RDF Turtle syntax then the data was stored in MongoDB. The knowledge graph constructed by Coding Staple API GraphQL. The knowledge graph queried the graphQL and rendered knowledge graph via Vis.js. HTML, CSS and JS deployed for the front-end user access. The study utilized various technologies, such as MongoDB Atlas, Staple API and IDE. A prototype knowledge graph was developed. A five-point Likert scale was used for the system’s evaluation. The attributes evaluated were user satisfaction, efficiency and learnability. The average scores obtained for the user satisfaction, efficiency and learnability were 4.70, 4.21 and 3.71, respectively. The scores show that the users rated the system high.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Electronic library, Electronic resources, Graphql, Knowledge graph, Ontology, Semantics
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Mrs Patricia Nwokealisi
Date Deposited: 15 Nov 2021 13:20
Last Modified: 15 Nov 2021 13:20

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