KMSBOT: enhancing educational institutions with an AI-powered semantic search engine and graph database
- Title
- KMSBOT: enhancing educational institutions with an AI-powered semantic search engine and graph database
- Creator
- Subramanian D.V.; Chandra J.; Immanuel V.A.; Rohini V.
- Description
- In the rapidly evolving field of education, a semantic search engine is essential to efficiently retrieve knowledge experts data. Universities and colleges continuously generate a vast amount of educational and research data. A semantic search engine can assist students and staff in efficiently searching for required information in such a big data pool. The existing systems have limitations in providing personalized recommendations that align with the individual learning objectives of students and scholars, thus hindering their educational experience. To address this, this paper proposed a KMSBOT. This novel recommendation system effectively summarizes academic data and provides tailored information for students, research scholars, and faculty, enhancing educational experiences. This paper meticulously details the development of KMSBOT, which comprises a neo4j-based knowledge graph technique, the NLP method for data structuring, and the KNN machine learning model for classification. The system employs a three-module approach, utilizing data structuring, NLP processing, and semantic search engine integration. By leveraging Neo4j, NLTK, and BERT in Python, this proposed work ensures optimal performance metrics such as time, accuracy, and loss value. The proposed solution addresses traditional recommendation systems limitations and contributes to a brighter future, improving user satisfaction and engagement in academic environments. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
- Source
- Soft Computing
- Date
- 2024-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Educational search engine; Natural language process; Neo4j; Recommendation system; Text processing
- Coverage
- Subramanian D.V., Department of Computer Science, Christ University, Bengaluru, India; Chandra J., Department of Computer Science, Christ University, Karnataka, Bengaluru, India; Immanuel V.A., Department of Computer Science, Christ University, Bengaluru, India; Rohini V., Department of Computer Science, Christ University, Karnataka, Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISSN: 14327643
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Subramanian D.V.; Chandra J.; Immanuel V.A.; Rohini V., “KMSBOT: enhancing educational institutions with an AI-powered semantic search engine and graph database,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/13393.