ABSTRACT
In a broad sense, natural language processing (NLP) may be defined as the capacity of a set of computer instructions to be familiar with human interpretation language as a part of artificial intelligence (AI). In general, it may be concerned more precisely towards coding to process and analyze a huge amount of data. Somehow, Challenges in NLP may involve with speech recognition, understanding natural language as well as generating natural language. In the present scenario, it has been more focused on in supervised and semi-supervised learning techniques. In such cases, the algorithms associated with such techniques may be able to learn from data using a combination of annotated and non-annotated data. Practically, it may be too difficult and may produce less accurate results for a given amount of input data.
98The primary intention of NLP may be linked to accomplish human-like language processing. Choosing the word during performance may be very deliberate, and may not be replaced with actual understanding. The complete perception of NLP may be associated with the following:
Making phrase and outlined the input text;
Conversion of the text into similar language in different form;
Queries about the text;
Inference from the text.
Considering the levels, it has been presumed that the levels of human language processing may be assigned in sequential manner and seems to be more dynamic. Accordingly, the information gained may also assist in lower level of analysis.
