NLTK – Use Cases

I was venturing to a new research on chatbots where I ended up with putting efforts on understanding NLTK which is a Natural  Language Processing Toolkit for Python. This toolkit helps to simplify the efforts related to NLP processing. There are excellent Youtube video tutorials on NLTK which you can look one by sentdex which has dealt a lot of sentiment analysis right from installation.

In this post I will attempt to share my thoughts on how we can use this NLTK to solve different use cases.

Recommendation: Recommendation of content can be made based on the similarity. Against similarity can be calculated based on semantic similarity and lexical similarity. Lot of more can be explored such as cosine similarity.

Sentiment Analysis:  Sentiment analysis can be used to determine the authors attitude on the content based on the good words dictionary by adopting simple scoring techniques.

N-Gram Analysis: By tokenizing the content we can analyze the content in large text for large text analysis.

NLTK is a very powerful tool, which can be used for extensive programming pertaining to natural text. It also has package called nltk.chat which could be used for building chatbots.

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