A Semantic Knowledge-Based Framework for Information Extraction and Exploration

Aljamel, Abduladem; Osman, Taha; Thakker, Dhavalkumar

Abstract

The availability of online documents that describe domain-specific information provides an opportunity in employing a knowledge-based approach in extracting information from web data. This research proposes a novel comprehensive semantic knowledge-based framework that helps to transform unstructured data to be easily exploited by data scientists. The resultant sematic knowledgebase is reasoned to infer new facts and classify events that might be of importance to end users. The target use case for the framework implementation was the financial domain, which represents an important class of dynamic applications that require the modelling of non-binary relations. Such complex relations are becoming increasingly common in the era of linked open data. This research in modelling and reasoning upon such relations is a further contribution of the proposed semantic framework, where non-binary relations are semantically modelled by adapting the semantic reasoning axioms to fit the intermediate resources in the N-ary relations requirements.

Citation

Aljamel, A., Osman, T., & Thakker, D. (2021). A Semantic Knowledge-Based Framework for Information Extraction and Exploration. International Journal of Decision Support System Technology, 13(2), 85--109. https://doi.org/10.4018/IJDSST.2021040105

• Journal Article Type: Article
• Acceptance Date: Apr 1, 2021
• Online Publication Date: Apr 1, 2021
• Publication Date: Jan 1, 2021
• Deposit Date: Dec 10, 2024
• Publicly Available Date: Dec 10, 2024
• Journal: International Journal of Decision Support System Technology (IJDSST)
• Print ISSN: 1941-6296
• Electronic ISSN: 1941-630X
• Publisher: IGI Global
• Peer Reviewed: Peer Reviewed
• Volume: 13
• Issue: 2
• Pages: 85--109
• DOI: https://doi.org/10.4018/IJDSST.2021040105
• Keywords: Information extraction; Knowledge representation; Knowledge-based approach; Machine learning; Natural language processing; Non-binary relations; Open linked data; Semantic web technologies
• Public URL: https://hull-repository.worktribe.com/output/4099630