Computer Science & IT
Coding & Algorithms Development
Computer Science & IT
Shrewd Object Visualization Mechanism
AI For Cybersecurity and Knowledge Breach
Machine Learning in Hyperautomation
The Intersection of ML and IoT
Consistent Integration with Other Languages
Natural Language Processing
Latest to foray into the world of technology is Natural Language Processing (NLP), a technology that aids computers to comprehend the human’s natural language. NLP is a branch of Artificial Intelligence, and the objective of this technology is to read, decipher, and make sense of the human languages in a way that is valuable. NLP depends on machine learning to bring out the implications from human languages.
NLP acts behind many common applications such as Google Translate. Word Processors and Grammarly employ NLP to check accuracy of grammar in texts. Even the Interactive Voice Response (IVR) applications used in call centers rely on NLP. All Personal assistant applications that are available such as Cortana and Alexa make use of NLP.
NLP is rather a challenge because of the complexity of the human language. Natural languages are ambiguous and imprecise which make NLP difficult. NLP necessitates applying algorithms to recognize and mine the natural language rubrics so that the formless language data is converted into a form that computers understand. Sometimes, the computer may fail leading to vague results. The two main techniques for NLP are semantic analysis and syntactic analysis. With more research being carried out in this field, more breakthroughs are expected in NLP.
Source: bold360.com
References
Qi, P., Zhang, Y., Zhang, Y., Bolton, J., & Manning, C. D. (2020). Stanza: A Python natural language processing toolkit for many human languages. arXiv preprint arXiv:2003.07082.
Wolf, T., Chaumond, J., Debut, L., Sanh, V., Delangue, C., Moi, A., & Rush, A. M. (2020, October). Transformers: State-of-the-art natural language processing. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations(pp. 38-45).
