Day #210 - NLP Coding Snippets

Samples on Entity Extraction, Keywords extraction, Sentiment Analysis for evaluating sentences.

	#pip install spacy
	#python -m spacy download en
	#pip install multi-rake
	from multi_rake import Rake
	import spacy
	nlp = spacy.load('en')
	from textblob import TextBlob
	def computekeywords(sentence):
	print(sentence)
	doc = nlp(sentence)
	rake = Rake()
	print('using spacy')
	for ent in doc.ents:
	print(ent.text, ent.label_)
	keywords = rake.apply(sentence)
	print('Keywords using Rake')
	print(keywords)
	print('Sentiment of the sentence')
	analysis = TextBlob(sentence)
	if(analysis.sentiment[0])>0:
	intent = 'Positive'
	elif(analysis.sentiment[0])<0:
	intent = 'Negative'
	else:
	intent = 'Neutral'
	print(intent)
	sentence = "I need car insurance"
	computekeywords(sentence)
	sentence2 = "I lost my credit card"
	computekeywords(sentence2)
	#I need car insurance
	#using spacy
	#Keywords using Rake
	#[('car insurance', 4.0)]
	#Sentiment of the sentence
	#Neutral
	#I lost my credit card
	#using spacy
	#Keywords using Rake
	#[('credit card', 4.0), ('lost', 1.0)]
	#Sentiment of the sentence
	#Neutral

view raw NLP_Keywords.py hosted with ❤ by GitHub

Happy Mastering DL!!!!