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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM36789
Volume:
8 |
7 |
Jul 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Managing large amounts of data can be challenging in this era. Information Extraction and Ontology Learning are two vital technologies that address this difficulty. IE automatically retrieves and utilizes required data from unstructured data, using Named Entity Recognition techniques. OL is used to construct a formal representation of knowledge by organizing data into concepts and relationships between them based on the specific domain. These technologies enhance data organization, searchability, and interoperability, and when combined, they enable effective data analysis, tailored services, and the development of intelligent systems. They also play a vital role in advancing e-learning, as they retrieve and structure information related to the education sector, providing more organized and personalized efficient details for students and users. By leveraging IE and OL, educators can better align learning materials with student needs and track educational trends, improving the overall learning experience.
KEYWORDS
Publication Date
7/24/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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