About Prachi Kumar

Prachi is a graduate student in Computer Science at the University of California, Los Angeles. Her interests lie in the fields of Data Mining, Machine Learning and Natural Language Processing.

The Power of WordNet and How to Use It in Python

In this post, I am going to talk about the relations in WordNet (https://wordnet.princeton.edu) and how you can use these in a Python project. WordNet is a database of English words with different relations between the words.

Take a look at the next four sentences.

  1.  “She went home and had pasta.”
  2. “Then she cleaned the kitchen and sat on the sofa.”
  3. “A little while later, she got up from the couch.”
  4. “She walked to her bed and in a few minutes she was snoring loudly.”

In Natural Language Processing, we try to use computer programs to find the meaning of sentences. In the above four sentences, with the help of WordNet, a computer program will be able to identify the following –

  1. “pasta” is a type of dish.
  2. “kitchen” is a part of “home”.
  3. “sofa” is the same thing as “couch”.
  4. “snoring” implies “sleeping”.

Let’s get started with using WordNet in Python. It is included as a part of the NLTK (http://www.nltk.org/) corpus. To use it, we need to import it first.

>>> from nltk.corpus import wordnet as wn

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Build your own Natural Language Processing based Intelligent Assistant using Python, It’s easy!

Before we begin, let us talk about how Mike (a fictional character) spends a typical morning. Mike begins his day by searching for breakfast recipes on Google Now (https://en.wikipedia.org/wiki/Google_Now). After a filling breakfast, Mike starts getting ready for work. He asks Siri (http://www.apple.com/in/ios/siri/) to tell him the weather and traffic conditions for his drive to work. Finally, as Mike gets ready to leave the house, he asks Alexa (https://en.wikipedia.org/wiki/Amazon_Alexa) to dim the lights and thermostat. It is not even 10 a.m. yet, but Mike like many of us has already used three intelligent personal assistant applications using Natural Language Processing (NLP). We will unravel the mysteries of building intelligent personal assistants with a simple example to build such an assistant quite easily using NLP.

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