keyword-extraction-textrank-18.py

def evaluate_micro_average(actual_keys,predicted_keys):
  # Combining actual keywords
  ground_truth=[]
  for i in actual_keys:
    ground_truth.extend(i)
  
  # Combining extracted keywords
  extracted_keywords=[]
  for i in predicted_keys:
    extracted_keywords.extend(i)

  # Number of extracted keywords
  num_extract=len(extracted_keywords)
  # Number of keywords in ground truth
  num_actual=len(ground_truth)
  # Number of correctly extracted keywords
  num_correct=0
  for i,j in zip(actual_keys, predicted_keys):
    num_correct+=len(set(i).intersection(set(j)))

  # If no correct keywords were extracted
  if num_correct==0:
    return [0,0,0]

  # Precision
  precision=num_correct/num_extract

  # Recall
  recall=num_correct/num_actual

  # F-measure
  Fmeasure=(2*precision*recall)/(precision+recall)

  return precision*100,recall*100,Fmeasure*100