Comparative Study of AI‑Based and Traditional Research Paper Classification Methods in Ibrahim Badamasi Babangida University, Lapai, Niger State
- Project Research
- 1-5 Chapters
- Abstract : Available
- Table of Content: Available
- Reference Style:
- Recommended for :
- NGN 5000
Background of the Study
Accurate classification of research papers is essential for efficient information retrieval and academic knowledge dissemination. At Ibrahim Badamasi Babangida University, Lapai, Niger State, both AI‑based and traditional classification methods are used to organize scholarly works. Traditional methods, reliant on manual indexing and keyword tagging, often suffer from subjectivity and inconsistency. In contrast, AI‑based systems employ machine learning and natural language processing to automate the classification process. These systems can analyze text content, citation patterns, and semantic structures to categorize research papers more objectively (Olawale, 2023; Musa, 2024). By comparing the two approaches, this study aims to evaluate the accuracy, speed, and reliability of AI-driven methods relative to conventional techniques. The AI approach offers significant advantages in processing large volumes of data quickly and can adapt to new terminologies and interdisciplinary research areas. However, challenges such as algorithmic bias and the need for high-quality training datasets persist. The background discussion also examines case studies from other institutions where AI classification has been implemented, highlighting improvements in retrieval efficiency and user satisfaction. The integration of AI in research paper classification represents a crucial step towards modernizing academic libraries and supporting effective research collaboration. As digital repositories continue to expand, the need for automated, scalable, and reliable classification methods becomes increasingly important. This study provides a comprehensive review of both AI-based and traditional classification methods, setting the stage for a comparative analysis that will inform best practices in academic information management (Ibrahim, 2025).
Statement of the Problem
The current research paper classification system at Ibrahim Badamasi Babangida University relies heavily on manual processes that are time-consuming and prone to inconsistencies. Traditional methods often result in misclassification and delayed indexing, thereby impeding efficient information retrieval for researchers. Although AI‑based classification systems promise enhanced accuracy and speed, their implementation is challenged by issues such as inadequate training data, potential algorithmic biases, and the complexities of integrating new systems with existing digital libraries (Chinwe, 2023). Faculty and librarians have raised concerns about the transparency of AI decision-making processes and the potential loss of expert judgment. Moreover, the lack of standardized evaluation metrics for comparing the performance of AI-based and traditional methods further complicates the transition. This study seeks to address these challenges by conducting a rigorous comparative analysis of both systems. The research will measure performance indicators such as classification accuracy, processing time, and user satisfaction. By identifying the shortcomings and advantages of each approach, the study aims to propose a hybrid model that leverages the strengths of AI while retaining the nuanced insights provided by human experts. This investigation is critical for ensuring that the university’s digital library remains efficient, reliable, and up-to-date in its classification of scholarly research (Adebayo, 2024).
Objectives of the Study
-
To compare the accuracy and efficiency of AI-based and traditional classification methods.
-
To identify key challenges associated with the implementation of AI systems.
-
To propose a hybrid classification model that integrates AI with expert oversight.
Research Questions
-
How does the accuracy of AI-based classification compare to traditional manual methods?
-
What are the main challenges in implementing AI classification in academic libraries?
-
Which features of both approaches can be integrated for optimal performance?
Significance of the Study
This study is significant as it provides a comparative analysis of research paper classification methods at Ibrahim Badamasi Babangida University. By highlighting the benefits and limitations of AI-based systems versus traditional methods, the research aims to guide the development of more efficient, accurate, and user-friendly classification models. The findings will inform digital library strategies and enhance research accessibility (Olayinka, 2024).
Scope and Limitations of the Study
This study is limited to comparing research paper classification methods at Ibrahim Badamasi Babangida University and does not extend to other library functions.
Definitions of Terms
-
Classification Methods: Techniques used to organize and categorize academic research.
-
Machine Learning: A subset of AI that enables systems to learn patterns from data.
-
Digital Libraries: Online repositories that store and manage scholarly resources.
Related Project Materials
EFFECT OF HUMAN CAPITAL DEVELOPMENT ON ORGANIZATIONAL PERFORMANCE
ABSTRACT
This study was carried out to examine the effect of human capital development on organization...
An Assessment of the Effectiveness of Mental Health Support Programs in Taraba State
Background of the Study
Mental health issues are a growing concern globally, and in Nigeria, there remains a significant gap in mental he...
An Examination of Marketing Mix Strategies and Their Impact on Small Business Success: A Case Study of Clothing Retailers in Kaduna State
Background of the Study
Marketing mix strategies are essential for small businesses, especially in the competitive retail s...
A critical analysis of talent management strategies in driving business growth: A study of manufacturing firms in Nasarawa State
Background of the Study
Talent management is a critical aspect of organizational success, particularly in industries like manufacturing,...
An examination of the role of open access repositories in research archiving in Ekiti State Polytechnic, Isan-Ekiti, Ekiti State
Background of the Study:
Effective research archiving is essential for preserving academic output and ensuring long-term ac...
THE ROLE OF FUND ACCOUNTANTS IN FUND ADMINISTRATION
Abstract: THE ROLE OF FUND ACCOUNTANTS IN FUND ADMINISTRATION
This study aims to: (1) evaluate the role of fund accountants in fund admin...
BUSINESS EDUCATION TEACHERS’ PERCEPTIONS REGARDING THE STRUCTURE OF JSC BUSINESS STUDIES EXAMINATION
ABSTRACT
The study was aimed at ascertaining Business Education teacher’s perceptions regard...
The effect of peer tutoring on students' academic achievement in secondary schools in Mangu LGA, Plateau State
Background of the Study
Peer tutoring, a collaborative learning strategy where students support one another’s academi...
The Effect of Nurse-Led Parental Education on Childhood Disease Prevention in Kaduna State
Background of the Study: Childhood diseases such as malaria, diarrhea, and respiratory infections are leadin...
The effect of interest rate stability on deposit growth in banking: a case study of Fortis Microfinance Bank
Background of the Study
Interest rate stability is a cornerstone of deposit mobilization in the banking sector. Fortis Microfinance Bank...
