fuzzy_logic_tagging

fuzzy_logic_tagging_eng3.py

def fuzzy_tagging(tags, articles):
	"""
	This function receives as input a list of predefined tags and the list of textual content to be tagged.
  Returns a Pandas dataframe with the articles tagged
	"""
	results = []
	# iterate through tags
	for i, tag in enumerate(tags):
	    d = {}
	    ranking = process.extract(tag, articles, limit=4) # extract the tag, ranking the 4 articles most representative
	    for r in ranking:
	        d = {"tag": tag, "index": articles.index(r[0]), "confidence": r[1]}
	        results.append(d)
	# organize everything in a pandas dataframe
	raw_tags = pd.DataFrame(results)
	raw_tags.set_index('index', inplace=True, drop=True)

	d = {}
	for i, row in raw_tags.iterrows():
	    if d.get(i):
	        if row['confidence'] >= 55: # if the threshold exceeds the value of 55
	            d[i] += ', ' + str(row['tag'])
	    else:
	        d[i] = str(row['tag'])
	        
	# create the final dataset
	tags = pd.Series(d, name='tag')
	tagged_df = pd.concat([posts, tags], axis=1)
	
	return tagged_df