Natural Language Processing for Boosting Text Related Data Retrieval from Larger Repositories Using Python

  • Ms. N Anuradha, Dr. P. Vijaya Pal Reddy, Ms. Anitha Vemulapalli

Abstract

Natural Language Processing (NLP) is a sub-domain of Artificial Intelligence and is most focused area in research and development. Now NLP spread to web applications on internet. It is related to English like language, now it is spreading its wings towards other languages. There is lot of space when we combine Natural Language Processing with Deep Learning Techniques. Data Science plays a key role in the domain of Natural Language Processing, which comes under the umbrella of Artificial Intelligence. The model is obtained from the Data Science to know something worth in learning from people who interested in the web searches. By combining artificial intelligence, computer science and engineering and Natural Language Processing (NLP) helps computer systems or machines read by simulating the human ability to understand the language. For most set the question which is in mind, collect the data based on that question and apply Natural Language Processing techniques with the help of python language. Data gathering and cleaning is the important process. After clean we maintain Document-Term Matrix(DTM). DTM data we train machine by creating machine learning algorithms. Python language is user-friend language which can give bulk of data then the normal search.

Published
2020-05-07
How to Cite
Ms. N Anuradha, Dr. P. Vijaya Pal Reddy, Ms. Anitha Vemulapalli. (2020). Natural Language Processing for Boosting Text Related Data Retrieval from Larger Repositories Using Python. International Journal of Advanced Science and Technology, 29(06), 3523 - 3528. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/14152