Browsing by Author "Mabayoje, M. A."

Now showing 1 - 7 of 7
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    Borrowing patterns monitoring in Library: Application of Apriori algorithm
    (International Journal of Information Processing and Communication, 2015) Adewole, K. S.; Akintola, A. G.; Mabayoje, M. A.; Ogbomon, G. A.
    Data is a valuable tool for any institution, and with the world advancing in technology, data stored in database management systems are growing in different capacities in almost all organization. The opportunities of database management systems have been explored. However, many organizations have not been able to leverage these opportunities in gaining business intelligence from their repositories. This paper addresses the issue of knowledge discovery from large databases using association rule mining. Apriori algorithm is implemented to discover hidden knowledge from a library database. Data depicting nine (9) different books were used within forty-seven (47) unique transactions. Eighteen (18) unique transactions were generated from the database showing the borrowing pattern of library users. The frequencies of borrowing of books were obtained as well as the associations. The result shows that borrowing a particular book may leads to borrowing another book as revealed in the association between Data structure in C (DS) textbook and Programming in C (C) textbook. The discovered pattern can help librarians in restructuring their bookshelf arrangement, and for book recommendation system. This system can also help students to have good knowledge different related books.
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    Development of an Efficient Onotological Algorithm for Information Retrieval
    (The Zambia Library Association Journal, 2015) Mabayoje, M. A.; Sadiku, J.S.; Olabiyisi, S.O.
    The amount of content stored and shared on the Web and other document repositories is increasing fast and continuously. This enlargement results in well-known difficulties and problems, such as finding and properly managing all the existing amount of information. Recordable progress has been achieved in the last decade with the development of search engine technologies, which collect, store and pre-process this information to return relevant resources in response to users’ needs. Nevertheless, users still need extra efforts sometimes to reach their targets, even if the retrieved information is present in the search space. The motivation for Semantic Web has been a search model which employs the use of semantics for Information Retrieval. In this paper, an efficient algorithm using full ontology for Knowledge Based (KB) to improve search over large documents stored on the web or other repositories is proposed. The approach employs ontology Knowledge Based (KB) as document repository for fast retrieval, automatic semantic indexing based on Ontology KB for both upper-level and domain specific. Also, integration of Query Expansion was employed as to unbind all constraints of original user’s query for better retrieval system performance. It was concluded that the added value of semantic information retrieval over traditional keyword-based retrieval has helped to achieve better precision through query weight and better recall through semantic relations. The proposed algorithm is robust, flexible and efficient. The algorithm can be useful in digital libraries, information filtering, media search and search engines. Keywords: Algorithm, Ontology, Informational Retrieval, Semantic, Domain Specific, Web.
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    Graphical Analysis of Road Crashes in Kwara State using Data Mining Approach
    (Faculty of Communication and Information Sciences, University of Ilorin, Ilorin., 2017) Olagunju, M.; Deniyi, A. E.; Mabayoje, M. A.
    Road accident is very common nowadays due to bad roads and some other factors such as intake of alcohol, overspeed and inexperience of the drivers. The main objective of this project is to analyze the trends in relation to a number of people survived, injured and category of people involved (either youths or adults). This study uses decision tree in data mining couple with data analysis which was carried out with SPSS. This study will definitely assist the road users and government to measure the trends of accidents within the given period.
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    Office Application in Digital Skill Acquisition, GNS 312,
    (General Studies Division, University of Ilorin, 2017) Jimoh, R. G.; Ahmed, M. I.,; Mabayoje, M. A.; AbdulRaheem, M.; Salihu, S. A
    GNS NOTE
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    Predicting Nigeria Budget Allocation Using Regression Analysis: A Data Mining Approach
    (The Journal of Computer Science and Its Applications, 2014) Adewole, K. S.; Mabayoje, M. A.; Abdulsalam, S. O.; Ajao, J. F.
    Budget is used by the Government as a guiding tool for planning and management of its resources to aid in effective decision-making. Data mining is one of the most vital areas of research with the objective of finding meaningful information from large datasets. The delay in the preparation of budget of the Federation by the Government has become incessant issue in the running of affairs of the country. This is evident in the delay in implementation of the previous budgets in the country; hence, the need for automated system to tackle the setback. In this paper, regression analysis which is one of the data mining techniques is employed to predict budget allocation from Nigeria budget dataset. 200 records consisting of the budget allocation summary for the year 2008, 2009, 2010, 2011, and 2012 across 40 data points containing Ministries, Departments, Commissions and Agencies (MDCAs) were used. A web-based data mining tool that employed linear regression to predict both Nigeria budget allocation across the 40 data points and the overall budget summary allocation of the Federation is proposed. The proposed data mining software predicted N1,803,196,024,657.40, N1,871,754,338,112.68 and N2,007,780,403,902.98 for the year 2013, 2014 and 2015 respectively. The tool is found capable of discovering interesting patterns in the data and for predicting budget allocation.
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    SOLVING THE NEXT RELEASE PROBLEM USING A HYBRID METAHEURISTIC
    (Tibiscus University, Romania., 2016) Balogun, A. O.; Mabayoje, M. A.; Makinwa, M. O.; Bajeh, A. O.
    The Next Release Problem is characterized by the need to determine the features that are to be included in a particular software system to make up the next release. These features are to be selected, such that users’ demands and needs are satisfied as much as possible, given a limited resources, by ensuring that the available resources are used to develop the most important features first. This work applies a hybrid of Variable Neighbourhood Search (VNS) and Tabu Search (TS) for solving bi-objective NRP, using a cost-value model for requirements. Experiments showed the hybrid metaheuristics to produce a Pareto optimal set with a controllable dynamic number of options whose score and cost value range can be controlled via parameters that can be modified without a significant effect on execution time.
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    Student Web Self-Service Portal for a Tertiary Institution
    (Covenant Journal of Informatics & Communication Technology (CJICT), 2016) Akintola, A. G.; Adewole, K. S.; Mabayoje, M. A.; Oke, J. O.
    The optimum condition for students to study is in an environment where they can access virtually all they need to know about courses, lecturers, locate places (for fresh and prospective students), validate staff identity, access past examination questions easily, identify vacant student hostels within and outside the school premises. Some of the reasons for students’ failure can be attributed to finding accommodation within or outside the school premises. Also, fresh students find it difficult to locate specific places in the university environment and some students find it very difficult to interact with staff. This paper presents a student self-service portal to address some of these challenges. Unified Modeling Language (UML) was used to model the system. The model was implemented using Microsoft C#, Microsoft ASP.net, Microsoft SQL Server, and Google Map. The proposed system was tested and the result obtained during the execution shows that the system is capable of addressing some of the challenges confronted by students.