CareerAlly: An Intelligent NLP-Driven Chatbot

In the current dynamic job market, career success depends on aligning skills with the evolving demands of specific job roles. However, many job-seekers struggle to identify skill gaps and assess their readiness for desired roles. Traditional methods lack a well-defined approach to self-evaluation, leaving candidates uncertain about necessary improvements. This research presents CareerAlly, an intelligent Chatbot designed to assist users in identifying skill gaps and strengthening their competencies for targeted job roles. As a solution, the Chatbot processes the user’s resume as input, applying natural language processing (NLP) techniques such as Named-Entity Recognition (NER) and Regular Expressions (regex) to extract relevant skills. CareerAlly then maps these extracted skills against a predefined job role-skill database (Jobmatcher) to identify deficiencies. To evaluate the user’s expertise, the Chatbot uses a Large Language Model (LLM) to generate skill-specific multiple-choice questions (MCQs) for the chosen job role, enabling objective knowledge assessment. Finally, CareerAlly provides users with a report that visualizes skill-based performance. The Chatbot uses Knowledge Graphs (neo4j) to recommend learning resources for job preparation. CareerAlly’s Artificial Intelligence (AI)-driven methodology offers systematic career guidance and supports users in addressing skill gaps, helping them improve their professional qualifications in a competitive job market. It will help individuals make informed decisions, enhance their competencies, and align their skills with industry demands. In effect, it will increase their employability.

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Publication Details

Published
2025-03-06
DOI
https://doi.org/10.1109/icoeca66273.2025.00019
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
2.48
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article

CareerAlly: An Intelligent NLP-Driven Chatbot

Aparna Iyer, Mayur Gaikwad, Aniket Kailas Shahade, Richa Shukla et al.
1 citations
AI in Service Interactions
2.48
article

CareerAlly: An Intelligent NLP-Driven Chatbot

Aparna Iyer, Mayur Gaikwad, Aniket Kailas Shahade, Richa Shukla, Anchal Sachan, S. Hevardhan
article en
1 citations

Abstract

In the current dynamic job market, career success depends on aligning skills with the evolving demands of specific job roles. However, many job-seekers struggle to identify skill gaps and assess their readiness for desired roles. Traditional methods lack a well-defined approach to self-evaluation, leaving candidates uncertain about necessary improvements. This research presents CareerAlly, an intelligent Chatbot designed to assist users in identifying skill gaps and strengthening their competencies for targeted job roles. As a solution, the Chatbot processes the user’s resume as input, applying natural language processing (NLP) techniques such as Named-Entity Recognition (NER) and Regular Expressions (regex) to extract relevant skills. CareerAlly then maps these extracted skills against a predefined job role-skill database (Jobmatcher) to identify deficiencies. To evaluate the user’s expertise, the Chatbot uses a Large Language Model (LLM) to generate skill-specific multiple-choice questions (MCQs) for the chosen job role, enabling objective knowledge assessment. Finally, CareerAlly provides users with a report that visualizes skill-based performance. The Chatbot uses Knowledge Graphs (neo4j) to recommend learning resources for job preparation. CareerAlly’s Artificial Intelligence (AI)-driven methodology offers systematic career guidance and supports users in addressing skill gaps, helping them improve their professional qualifications in a competitive job market. It will help individuals make informed decisions, enhance their competencies, and align their skills with industry demands. In effect, it will increase their employability.

Symbiosis International University (IN)
Openalex Percentile: Top 9%
AI in Service Interactions
2.48
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