Optimization of E-Library Search Engines Using AI-Based Semantic Search: A Case Study of Federal Polytechnic, Idah (Idah LGA, Kogi State)
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- 1-5 Chapters
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- Table of Content: Available
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- NGN 5000
Background of the Study
The advancement of digital libraries has revolutionized the way academic resources are accessed. However, many e-libraries still rely on keyword-based search engines, which often fail to deliver relevant results, especially when users search for complex or ambiguous terms (Kumar & Thompson, 2024). Traditional search engines are limited by their reliance on exact keyword matches, which may not capture the true meaning of a query or account for synonyms, context, or variations in phrasing (Jackson et al., 2025). In contrast, AI-based semantic search engines can understand the intent behind a user's query and return more accurate and contextually relevant results by analyzing the meaning of the search terms rather than just matching keywords.
Federal Polytechnic, Idah, in Kogi State, presents an opportunity to optimize its e-library search engine using AI-based semantic search technology. By applying AI algorithms that analyze natural language processing (NLP) and deep learning techniques, the polytechnic can significantly enhance its e-library services, providing students and faculty with faster and more precise access to academic resources (Sharma & Gupta, 2023). This study aims to explore the potential of AI-based semantic search in improving the functionality of e-library systems and the overall academic experience at Federal Polytechnic, Idah.
Statement of the Problem
The current e-library search engine at Federal Polytechnic, Idah, is primarily based on keyword matching, which limits the accuracy and relevance of search results. Users often find it difficult to locate specific academic resources, leading to inefficiencies in research and learning (Edwards & Roberts, 2023). This study seeks to address this challenge by integrating AI-based semantic search technology to optimize the search process and improve the user experience.
Objectives of the Study
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To explore the potential of AI-based semantic search engines in optimizing e-library search functionalities at Federal Polytechnic, Idah.
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To evaluate the effectiveness of semantic search technology in improving search accuracy and relevance in an e-library setting.
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To assess the impact of AI-based semantic search on the overall academic performance of students and staff at Federal Polytechnic, Idah.
Research Questions
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How can AI-based semantic search technology optimize the search capabilities of e-libraries at Federal Polytechnic, Idah?
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What improvements in search accuracy and relevance can be achieved through the use of semantic search?
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How does the implementation of AI-based semantic search affect the academic experience of students and faculty?
Research Hypotheses
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AI-based semantic search engines will improve the accuracy and relevance of search results in the e-library at Federal Polytechnic, Idah.
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The implementation of semantic search will enhance the efficiency of research and learning for students and staff at the polytechnic.
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AI-based search optimization will contribute to an improvement in academic performance and resource utilization at Federal Polytechnic, Idah.
Significance of the Study
This study will provide valuable insights into the application of AI-based semantic search in academic libraries, contributing to the optimization of e-library services. By improving search functionalities, the findings can enhance the research experience for students and staff at Federal Polytechnic, Idah, and offer practical solutions for other academic institutions.
Scope and Limitations of the Study
The study will focus on the e-library search engine at Federal Polytechnic, Idah, located in Idah LGA, Kogi State, and will examine the implementation of AI-based semantic search technology. Limitations include the potential technical challenges in integrating AI algorithms into existing systems, as well as the limited scope of the study, which focuses primarily on search functionality and does not address other aspects of e-library services.
Definitions of Terms
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Semantic Search: A search technique that uses AI and natural language processing to understand the meaning behind a query and return more relevant results.
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E-Library: A digital platform that provides access to electronic academic resources, such as books, journals, articles, and databases.
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Natural Language Processing (NLP): A branch of AI that enables machines to understand, interpret, and respond to human language in a way that is meaningful and contextually appropriate.
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