International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 186 - Issue 14 |
Published: March 2024 |
Authors: Emmanuel Isika, Akintoba Akinwonmi, Oluyomi Akinyokun |
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Emmanuel Isika, Akintoba Akinwonmi, Oluyomi Akinyokun . A Case-Based Reasoning (CBR) Internship Placement Model. International Journal of Computer Applications. 186, 14 (March 2024), 9-14. DOI=10.5120/ijca2024923486
@article{ 10.5120/ijca2024923486, author = { Emmanuel Isika,Akintoba Akinwonmi,Oluyomi Akinyokun }, title = { A Case-Based Reasoning (CBR) Internship Placement Model }, journal = { International Journal of Computer Applications }, year = { 2024 }, volume = { 186 }, number = { 14 }, pages = { 9-14 }, doi = { 10.5120/ijca2024923486 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2024 %A Emmanuel Isika %A Akintoba Akinwonmi %A Oluyomi Akinyokun %T A Case-Based Reasoning (CBR) Internship Placement Model%T %J International Journal of Computer Applications %V 186 %N 14 %P 9-14 %R 10.5120/ijca2024923486 %I Foundation of Computer Science (FCS), NY, USA
Candidates are faced with numerous challenges when seeking internship especially in IT-based firms, the challenges include elongated time-frame resulting from the conventional search of placement among others. This research presents a platform through the design of a case-based reasoning (CBR) model which mitigates the challenges and facilitates internship placements for candidates. The aim is to alleviate intern-employer mapping dilemma. The research applies supervised machine learning techniques including data pre-processing, feature extraction, document similarity metrics, and knowledge-intensive CBR pattern matching to optimize matching between intern candidate vectors and employer criteria vectors. The system resultantly introduce an ML based personalized and efficient matching platform with real-time support, potentially improving outcomes for interns and companies within the same ecosystem.