Abstract
Lately, there has been a lot of debates and discussions going on about the H-1B visa procedures in the United States. Every year, millions of students and professionals from all across the globe migrate to the USA for higher education or better job opportunities. However, the recent changes and restrictions in the H-1B visa procedure are making it tough for the international applicants to make a firm decision of wishing to work in the United States with this sense of uncertainty. While there are too many papers and journals on the study of the immigration process at the United States or the H-1B visas, there is almost no research carried on this sector in the field of computer science. The paper aims to address this issue of H-1B visa eligibility outcome using different classification models and optimize them for better results.
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Prateek, Karun, S. (2019). Predicting the Outcome of H-1B Visa Eligibility. In: Bhatia, S., Tiwari, S., Mishra, K., Trivedi, M. (eds) Advances in Computer Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 924. Springer, Singapore. https://doi.org/10.1007/978-981-13-6861-5_31
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DOI: https://doi.org/10.1007/978-981-13-6861-5_31
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