Research Article

A Case-Based Reasoning (CBR) Internship Placement Model

by  Emmanuel Isika, Akintoba Akinwonmi, Oluyomi Akinyokun
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Issue 14
Published: March 2024
Authors: Emmanuel Isika, Akintoba Akinwonmi, Oluyomi Akinyokun
10.5120/ijca2024923486
PDF

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
Abstract

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.

References
  • Amala Deshpande, Deepika Khatri, Divya Deshpande, Prarthita Das, & Sujata Khedkar. (2016). Proposed system for resume analytics. International Journal of Engineering Research And, V5(11). https://doi.org/10.17577/ijertv5is110274
  • Bessadok, A., Abouzinadah, E., & Rabie, O. (2021). Analyzing students’ digital behavior in an e-learning environment within the Blackboard Learning Management System. Innovative and Intelligent Technology-Based Services for Smart Environments – Smart Sensing and Artificial Intelligence, 127-133. doi:10.1201/9781003181545-19
  • Espenakk, E., Knalstad, M. J., & Kofod-Petersen, A. (2019). Lazy learned screening for efficient recruitment. Case-Based Reasoning Research and Development, 64–78. https://doi.org/10.1007/978-3-030-29249-2_5
  • Dhende S, Aniket S, Sushil A, Akash S, Sudhir D, (2018), Candidate Hiring Through CV Analysis. International Research Journal of Engineering and Technology (IRJET). 5(5) pp. 3148-3149
  • Doshi B., Gandhi H., Jayadharan N., Patil M, (2019), Implementation of Online Portal for CV Analysis Using KNN Algorithm. International Journal for Research in Applied Science & Engineering Technology. 7(4): pp. 1435-1439
  • Ferddie Quiroz Canlas, (2021), Data Mining Model for Student Internship Placement Using Modified Case-Based Reasoning.
  • Gartner_Inc (2018) Understanding Gartner's hype cycles, Gartner. Available at: https://www.gartner.com/en/documents/3887767 (Accessed: January 6, 2023).
  • Győrödi, C.A. et al. (2022) ‘A comparative study of mongodb and document-based MySQL for Big Data Application Data Management’, Big Data and Cognitive Computing, 6(2), p. 49. doi:10.3390/bdcc6020049.
  • Hu, Y., & Spiro, R. J. (2021). Design for now, but with the future in mind: A “cognitive flexibility theory” perspective on online learning through the lens of moocs. Educational Technology Research and Development, 69(1), 373-378. doi:10.1007/s11423-020-09920-z
  • Internship (2022) Wikipedia. Wikimedia Foundation. Available at: https://en.wikipedia.org/wiki/Internship (Accessed: December 20, 2022).
  • Kumar, N., Gupta, M., Sharma, D., & Ofori, I. (2022). Technical job recommendation system using apis and web crawling. Computational Intelligence and Neuroscience, 2022, 1–11. https://doi.org/10.1155/2022/7797548
  • Naik, Poornima & Naik, Girish. (2020). BIG DATA TOOLS WHICH, WHEN AND HOW? (Volume V) (Hands-on Sessions with Advanced MongoDB Concepts).
  • Nasution, D., & Sitorus, Z. (2021, September 27). Enhance Web-Based Job Search Recommendation System of Hybrid-Based Recommendation | Nasution | Budapest International Research and Critics Institute-Journal (BIRCI-Journal). Enhance Web-Based Job Search Recommendation System of Hybrid-Based Recommendation | Nasution | Budapest International Research and Critics Institute-Journal (BIRCI-Journal). https://doi.org/10.33258/birci.v4i3.2579
  • Omonijo, D.O. et al. (2019) “The review of the Student Industrial Work Experience Scheme (SIWES) in four selected countries,” Academic Journal of Interdisciplinary Studies, 8(3). Available at: https://doi.org/10.36941/ajis-2019-0014.
  • Mayer-Schönberger, V. & Cukier, K. (2014), Big Data: A revolution that will transform how we live, work, and think. Eamon Dolan/Mariner Books, USA.
  • Mayer-Schönberger, V. & Cukier, K. (2014). Learning with Big Data: the future of education. Boston/New York: Eamon Dolan Book.
  • Moore, K. (2022) Beyond chatgpt: The future of AI at work, Forbes. Forbes Magazine.Available at:https://www.forbes.com/sites/karlmoore/2022/12/14/leverage-generative-ai-workplace-tools-with-semantic-research/?sh=755aa89b771e (Accessed: January 6, 2023).
  • Pombo L., (2019), Landing on the right job: a machine learning approach to match candidates with jobs applying semantic embeddings. Master’s Thesis. Universidade Nova de Lisboa.
  • Pradhan, R., Varshney, J., Goyal, K., & Kumari, L. (2021). Job recommendation system using content and collaborative-based filtering. Advances in Intelligent Systems and Computing, 575–583. https://doi.org/10.1007/978-981-16-2594-7_47
  • Rea, J., & Gopalan, A. (2021). Word2Mouth - an eLearning platform catered for low-income countries. 2021 IEEE Global Engineering Education Conference (EDUCON). doi:10.1109/educon46332.2021.9454087
  • React (JavaScript library) (2022) Wikipedia. Wikimedia Foundation. Available at: https://en.wikipedia.org/wiki/React_(JavaScript_library) (Accessed: December 19, 2022).
  • Shalaby, W., AlAila, B. E., Korayem, M., Pournajaf, L., AlJadda, K., Quinn, S., & Zadrozny, W. (2017). Help me find a job: A graph-based approach for job recommendation at scale. 2017 IEEE International Conference on Big Data (Big Data). https://doi.org/10.1109/bigdata.2017.8258088
  • Slama, B.S. et al. (2021) Innovative and intelligent technology-based services for Smart Environments - smart sensing and Artificial Intelligence: Proceedings of the 2nd International Conference on Smart Innovation, ergonomics and applied human factors (SEAHF ’20), held online, 14-15 November 2020. Boca Raton: CRC Press.
  • Taylor, J.A. (2018) A brief history of the internship, Taylor Research Group.Taylor Research Group Available at: https://www.taylorresearchgroup.com/news/2017/4/5/a-brief-history-of-the-internship (Accessed: December 20, 2022).
  • Tomy, S., & Pardede, E. (2019). Map my career: Career planning tool to improve student satisfaction. IEEE Access, 7, 132950-132965. doi:10.1109/access.2019.2940986
  • Tomy, S., & Pardede, E. (2018). Course map: A career-driven course planning tool. Computational Science and Its Applications – ICCSA 2018, 185-198. doi:10.1007/978-3-319-95165-2_13
  • UNESCO, (2019), Artificial intelligence in education: challenges and opportunities for sustainable development.
  • Usage statistics and market share of react for websites (no date) W3Techs. Available at: https://w3techs.com/technologies/details/js-react (Accessed: December 19, 2022).
  • Vinay (2022) The importance of an internship: Top 5 reasons why internships are critical, Capital Placement. Available at: https://capital-placement.com/blog/the-importance-of-an-internship-top-5-reasons-why-internships-are-critical/ (Accessed: 23 July 2023).
  • What is Artificial Intelligence (AI) ? (no date) IBM. Available at: https://www.ibm.com/topics/artificial-intelligence (Accessed: January 6, 2023).
  • Ding, W. and Marchionini, G. 1997 A Study on Video Browsing Strategies. Technical Report. University of Maryland at College Park.
  • Fröhlich, B. and Plate, J. 2000. The cubic mouse: a new device for three-dimensional input. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
  • Tavel, P. 2007 Modeling and Simulation Design. AK Peters Ltd.
  • Sannella, M. J. 1994 Constraint Satisfaction and Debugging for Interactive User Interfaces. Doctoral Thesis. UMI Order Number: UMI Order No. GAX95-09398., University of Washington.
  • Forman, G. 2003. An extensive empirical study of feature selection metrics for text classification. J. Mach. Learn. Res. 3 (Mar. 2003), 1289-1305.
  • Brown, L. D., Hua, H., and Gao, C. 2003. A widget framework for augmented interaction in SCAPE.
  • Y.T. Yu, M.F. Lau, "A comparison of MC/DC, MUMCUT and several other coverage criteria for logical decisions", Journal of Systems and Software, 2005, in press.
  • Spector, A. Z. 1989. Achieving application requirements. In Distributed Systems, S. Mullender
Index Terms
Computer Science
Information Sciences
Machine Learning Case-Based Reasoning
Keywords

Machine Learning Internships Case-Based Reasoning Natural Language Processing

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