In text mining we tend to view free text as a bag of tokens (words, n-grams). In order to do various quantitative analyses, searching and information retrieval, this approach is quite useful. However, when we take a bag of tokens approach, we tend to lose lots of information contained in the free text, such as sentence structure, word order, and context. These are some of the attributes of natural language processing which humans use to interpret the meaning of given text. NLP is a field focused on understanding free text. It attempts to understand a document completely like a human reader.
POS tagging is a prerequisite and one of the most import steps in text analysis. POS tagging is the annotation of the words with the right POS tags, based on the context in which they appear, POS taggers categorize words based on what they mean in a sentence or in the order they appear. POS taggers provide information about the semantic meaning of the word. POS taggers use some...
