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Papers by Archana Maurya
Machine Translation (MT) is a crucial application of (NLP) Natural language Processing. This MT t... more Machine Translation (MT) is a crucial application of (NLP) Natural language Processing. This MT technique automatic and based on computers. One of the most modern techniques adopted in MT is machine learning (ML). Over the past few years, ML has grown in popularity during MT process among researchers. Ambiguity is a major challenge in MT. Word Sense Disambiguation (WSD) is a common technique for solving the ambiguity problem. ML approaches are commonly used for the WSD techniques and are used for training and testing purposes. The outcome prediction of the test data gives encouraging results. Text classification is one of the most significant techniques for resolving the WSD. In this paper, we have analyzed some common supervised ML text classification algorithms and also proposed a “hybrid model” called “AmbiF.” We have compared the results of all analyzed algorithms with the proposed model “AmbiF. The analyzed supervised algorithms are Decision Tree, Bayesian Network, Support Vect...
Proceedings of Second Doctoral Symposium on Computational Intelligence, 2021
Lecture notes in networks and systems, Nov 10, 2022
Machine Translation (MT) is a crucial application of (NLP) Natural language Processing. This MT t... more Machine Translation (MT) is a crucial application of (NLP) Natural language Processing. This MT technique automatic and based on computers. One of the most modern techniques adopted in MT is machine learning (ML). Over the past few years, ML has grown in popularity during MT process among researchers. Ambiguity is a major challenge in MT. Word Sense Disambiguation (WSD) is a common technique for solving the ambiguity problem. ML approaches are commonly used for the WSD techniques and are used for training and testing purposes. The outcome prediction of the test data gives encouraging results. Text classification is one of the most significant techniques for resolving the WSD. In this paper, we have analyzed some common supervised ML text classification algorithms and also proposed a “hybrid model” called “AmbiF.” We have compared the results of all analyzed algorithms with the proposed model “AmbiF. The analyzed supervised algorithms are Decision Tree, Bayesian Network, Support Vect...
Proceedings of Second Doctoral Symposium on Computational Intelligence, 2021
Lecture notes in networks and systems, Nov 10, 2022