def average_distance(cls, start: WSP, end: WSP):
total_distance = 0
for word in start.onyms:
if Word2Vec.contains(word):
total_distance += cls.distance(word, end.word)
average_distance = total_distance / len(start.onyms)
return average_distance
def wsp_similarity(cls, start: WSP, end: WSP):
total_vector = np.zeros(shape=(300, ), dtype=np.float32)
for word in start.onyms:
if Word2Vec.contains(word):
total_vector = np.add(Word2Vec.vector(word), total_vector)
Word2Vec.add_vector(start.name, total_vector)
return Word2Vec.similarity(start.name, end.word)
