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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM64787

TALENTMAP : INTELLIGENT CAREER MAPPING SYSTEM

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM64787

Volume:

10 |

6 |

Jun 2026

Pages:

1-7

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM64787

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

GVNSS

GADAM VENKATA NAGA SAI SINDHU

Master of Computer Applications

Giet Engineering College (A)

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Mentors

TM

T. MEENAKSHI

Master of Computer Applications

Giet Engineering College (A)

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Abstract

TalentMap: Intelligent Career Mapping System" is a Python/Flask web application designed to be used as an intelligent tool for analyzing resumes, extracting skills from resume information, predicting suitable jobs for the candidates and offering recommendations for personal career development. The system uses user-defined skills as well as other profile information provided by the user in his/her resume and maps it against the manually generated database of IT career roles. Based on similarities and skillset readiness of the candidate, the system provides suitable career path for the candidate. Moreover, in addition to mapping careers, the system recommends additional skills to be learned and determines skill gaps by comparing user skills with essential and intermediate skills needed for a particular job role chosen by the user. To further help users know how much they have to learn to advance their careers, a structured learning roadmap is offered by the system. Finally, the application supports user authentication, session management, history generation, and reporting features to make it more interactive and personalize the experience. Designed using Flask, SQLite, and skill comparison rules, the project focuses on explainable recommendations instead of predictions.

KEYWORDS

TalentMap career guidance resume-based analysis skill extraction job role prediction skill gap analysis learning roadmap Flask Python SQLite user authentication history tracking session management rule-based recommendation IT career mapping.

Cite This Article

GADAM VENKATA NAGA SAI SINDHU, T. MEENAKSHI, "TALENTMAP : INTELLIGENT CAREER MAPPING SYSTEM," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-7, Jun 2026. https://doi.org/10.55041/IJSREM64787

Full Article/Conclusion

Such an integrated approach to career advice offers users an easy way to improve their skills and acquire knowledge on how to be ready for working on their desired jobs. The system analyzes the user's readiness and provides him/her with an opportunity to become closer to the desired career. One of the strengths of the system under analysis is that the process starts with skill input based on resume analysis. In contrast to answering a question in a general manner, the analysis tool checks the skills of the user against the set of career roles and determines the most suitable ones. Gap analysis and readiness evaluation increase the meaning of the output as the user can determine the skills he/she lacks and his/her preparedness for the certain position. Further learning roadmap development allows making a concrete action plan and time evaluation shows the necessary efforts to succeed in resume-based career mapping.The system under consideration would be useful for students, unemployed people or even individuals who need career advice to work in the IT domain in the future. Its simple construction and workflow allow defining this system as effective.

References

[1]    X. Q. Ong and K. H. Lim, “SkillRec: A Data-Driven Approach to Job Skill Recommendation for Career Insights,” in 2023 15th International Conference on Computer and Automation Engineering (ICCAE), pp. 40–44, Feb. (2023)  [2]  A. Gugnani and H. Misra, “Implicit skills extraction using document embedding and its use in job recommendation,” in Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, no. 8, (2020).  [3]  W. E. Forum, “The future of jobs report 2020,” World Economic Forum, (2020). [4]  “A Machine Learning Approach to Career Path Choice for Information Technology Graduates,” Engineering, Technology & Applied Science Research, vol. 10, no. 6, (2020).  [5]  I. Khaouja, I. Kassou, and M. Ghogho, “A survey on skill identification from online job ads,” IEEE Access, vol. 9, (2021). [6]    A. P. and S. R., “Design of dynamic career path recommendation system based on user profile,” Journal of Information Technology Services, vol. 20, no. 3, pp. 57–73, (2021). [7]  J. Liu, Y. C. Ng, Z. Gui, T. Singhal, L. Blessing, K. L. Wood, and K. H. Lim, “Title2vec: a contextual job title embedding for occupational named entity recognition and other applications,” Journal of Big Data, vol. 9, no. 1, pp. 1–16, (2022). [8]  A. Barducci, S. Iannaccone, V. La Gatta, V. Moscato, G. Sperli, and S. Zavota, “An end-to-end framework for information extraction from Italian resumes,” Expert Systems with Applications, vol. 210, (2022).  [9]   Ao, G. Horváth, C. Sheng, Y. Song, and Y. Sun, “Skill requirements in job advertisements: A comparison of skill-categorization methods based on wage regressions,” Information Processing & Management, vol. 60, no. 2, (2023). [10]  A. R. S. and S. R., “A Privacy-Preserving, Explainable Job Recommendation System Using Transformer-Based NLP and Career Path Prediction,” SSRN, (2024).

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Publication Date

6/11/2026

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