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@article{198597,
        author = {SAJID KHAN and Hammad Shaikh and Dawood Shaikh and Ankit Thakur and Prof. Jagruti More},
        title = {Augmentation of the Anubandhan Job Portal to Make Skills Aspirational and Address Skill Gaps},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {9254-9257},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=198597},
        abstract = {Traditional job portals operate as static, one directional repository where candidates apply for positions with minimal feedback regarding their actual suitability. This lack of transparency leads to prolonged unemployment, increased candidate frustration, and a persistent mismatch between industry demands and academic output. This paper proposes a comprehensive augmentation of the Anubandhan job portal to transform it into an aspirational, Artificial Intelligence (AI)-driven career growth platform. By integrating Machine Learning (ML) and Generative AI architectures, the proposed system actively parses unstructured PDF resumes using regex-optimized Python libraries, mapping extracted data against a predefined, dynamically updatable skill taxonomy. The core recommendation engine utilizes the Term Frequency-Inverse Document Frequency (TF-IDF) statistical measure alongside Cosine Similarity to calculate a highly objective "Aspiration Match Score." This mathematical model isolates precise skill gaps and generates dynamic, personalized learning roadmaps. Furthermore, the portal introduces a Reverse ML Applicant Tracking System (ATS) that employs "Blind Screening" for bias-free employer talent discovery. To fully close the preparation loop, the system features a Voice-Activated Generative AI Mock Interview module utilizing the Google Gemini API to simulate real-time, technical HR screening. These augmentations bridge the critical gap between candidate capabilities and industry requirements, shifting the portal's paradigm from a mere listing board to an active, educational augmentation engine.},
        keywords = {Applicant Tracking System, Artificial Intelligence, Cosine Similarity, Generative AI, Machine Learning, Natural Language Processing, TF-IDF.},
        month = {April},
        }