Recent Challenges and Advancements in Natural Language Processing

In a recent development, Natural Language Processing has gained tremendous momentum and is one of the important areas of data science. It is a subset of Artificial Intelligence that translates the human understanding of language into a machine-understandable form and supports to accomplish repetitive jobs such as summarization, machine translation, etc. The use of NLP has multiplied since the development of AI bots like Alexa, Cortana, Siri, and Google Assistant. Along with numerous advancements from major corporations like Google, NLP has seen improvements in accuracy, speed, and even strategies that are used by computer scientists to handle challenging issues. Here are some of the important trends projected to dominate in the coming years for Natural Language Processing. With the growing need and demand for Artificial Intelligence, Machine Learning is projected to play a vibrant role, particularly in text analytics. With the help of supervised and unsupervised machine learning, a more thorough analysis can be done in the near future. The use of social media can be seen as one of the major platforms for all companies to make their decisions and can take a very significant role in it. With the help of many NLP tools, the company can identify customer reviews, feedback, and responses on social media. NLP is also anticipated to increase in popularity in fields that require the ability to comprehend user intent, such as semantic search and intelligent chatbots. The abundance of natural language technologies is anticipated to survive to shape the communication capability of cognitive computing along with the expanding application of deep learning and machine learning.

Keywords: Artificial intelligence, Deep learning, Machine learning, Natural language processing.