natural language processing

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What broadly distinguishes one domain from another? It is the named entities. It is essential to pick out entities from the text that you deal with for any useful NLP/NLU task.

In your NLP and Machine Learning tasks, as also research, getting the right detail from your voluminous text data is very important. You need a convenient, programmatic interface to your textual data.

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Using the right spellings shows good language skills. We often go wrong with our spellings and need a way to correct them. An automatic tool would help in this often overlooked task. North – a trie based spelling suggester helps you with some of your misspellings.

Follow a simple approach to specialize your model for a domain.

Reviews and ratings are everywhere. But are reviews consistent with ratings?

This is an easy-to-use multilingual text summarizer with a command line and a web interface. It lets you experiment with text summarization.

We look at two contrasting case studies.