In this post I would like to bring some of the most interesting applications of NLP.
1-An interesting subtask in NLP is POS or parts-of-speech of the language. In this task you try to associate part-of-speach—such as nouns, adjectives, verbs—to words in a text, based on context and relationship to adjacent words.
2- Another important task in NLP is coreference resolution. It is about understanding references to multiple entities existing in the text and disambiguating that reference.
For example the sentence “Obama told Joe Biden that he should consider running for president” is one of those phrases which contains coreferences (Joe Biden and he). This task is considered as a stepping stone in doing more complex tasks such as question answering and summarization
3- I also find quite useful the task of document summarization to automatically provide the most important points in the original document. This is particularly good for news summary.
4- Word sense disambiguation, for example the algorithm should distinguish between a mouse animal and a mouse input device as of picture below.
Other interesting applications are also the following
5-text categorization into specific domains for example spam - non spam emails or for detecting sexually explicit content ;
6- text clustering to automatically organize a set of documents. Lets say you have a folder of 200000 documents in .pdf and you want to organize them…. by hand. Go ahead and lets meet again in steemit on the year 2022
7- sentiment analysis to identify and extract subjective information in documents. Detect what your customers are saying about your company when they use social media.