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Nirmal kumar.S, Dr.B.Murugeshwari., Akhil Nair.R ,Rohini.C
» doi: 10.31838/ecb/2023.12.si6.409


Tribal communities often face significant challenges in accessing suitable employment opportunities that align with their skills and interests. By leveraging the power of Hadoop and AI technologies, it becomes possible to enhance the job matching process and bridge the gap between job seekers from tribal backgrounds and potential employers. Hadoop, a distributed data processing framework, enables the efficient storage and processing of large volumes of structured and unstructured data. By integrating AI techniques into this framework, it becomes feasible to analyze and extract valuable insights from diverse datasets, including job postings, resumes, and candidate profiles. Machine learning and AI algorithms can improve the job matching process even more. AI models can learn and detect patterns that result in effective job placements for tribal members by analyzing past data and user interactions. These models can then recommend acceptable employment prospects while taking into account a variety of elements, including location, salary, necessary skills, and cultural preferences. To help tribal job seekers gain the qualifications they need for desired professions, AI can also offer personalized recommendations for skill development and training programmers that are specific to their needs. Overall, the integration of Hadoop and AI technologies for job matching presents a promising solution to address the employment challenges faced by tribal people. By harnessing the power of data analytics and intelligent algorithms, this approach can facilitate meaningful job opportunities, empower individuals, and foster economic growth in tribal communities.

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