Randomness is important in many areas of natural language processing (NLP). It is useful in assisting learning algorithms, making better predictions, and generating more accurate models. Randomness is found in the data used to train and evaluate models.
We will use the LanguageTool API to demonstrate how to perform the spell-checking and grammar- checking of a document. Both of these tasks can be useful for NLP activities. LanguageTool supports several languages.
With the very significant amount of data being generated, it is useful to have a way of summarizing text. We will illustrate one approach for performing this task utilizing the summarizer API found at https://github.com/piravp/auto-summarizer.
Dictionaries, as supported by the MAP interface, are used for many NLP tasks. We will illustrate how they can be inverted using POS data...