def get_greatest_synsets_similarity_between(synsets_wn, nouns):
synset_wn_max = None
p_max = 0
if len(nouns) != 0:
for synset_wn in synsets_wn:
p_noun = 0
for noun in nouns:
synsets_of_noun = WordnetHandler.get_synsets_for_word(noun, 'n')
if len(synsets_of_noun) > 0:
p_each_noun = 0
for synset_of_noun in synsets_of_noun:
# p = synset_wn.path_similarity(synset_of_noun)
p = WordnetHandler.cal_similarity(synset_wn, synset_of_noun)
p_each_noun += p
p_each_noun = p_each_noun/len(synsets_of_noun)
p_noun += p_each_noun
p = p_noun/len(nouns)
if p > p_max:
synset_wn_max = synset_wn
else:
print "no nouns"
return synset_wn_max
def sim_2_word(word_1, word_2):
synsets_1 = synsets_for_word(word_1)
synsets_2 = synsets_for_word(word_2)
p_max = 0
if __WSD_type__ == 1:
for synset_1 in synsets_1:
for synset_2 in synsets_2:
p = WordnetHandler.cal_similarity(synset_1, synset_2)
if p > p_max:
p_max = p
if __WSD_type__ == 0:
if len(synsets_1) == 0 or len(synsets_2) == 0:
return 0
p_max = WordnetHandler.cal_similarity(synsets_1[0], synsets_2[0])
return p_max
def sim_for_synset_and_synsetvector(a_synset, vector):
p_max = 0
for (synset,weight) in vector:
p = WordnetHandler.cal_similarity(a_synset, synset)
if p is not None:
# p = p*weight
if p > p_max:
p_max = p
return p_max
def wordnet_based_synset(syn_wn, sen_ox):
sim = 0.0001
words_ox = split_words(sen_ox)
count = 0
for word in words_ox:
p_max = 0
synsets_1 = synsets_for_word(word)
for synset in synsets_1:
p = WordnetHandler.cal_similarity(synset, syn_wn)
if p > p_max:
p_max = p
if p_max != 0:
count += 1
sim += p_max
sim /= count + 0.001
return sim
def get_value_synset_for(cur_synset, synsets):
synsets_value = []
definition = cur_synset.definition()
nouns = PreprocessDefinition.preprocess_sentence(definition)
# nouns = list(set(nouns))
for synset in synsets:
count = 0
p = 0
for noun in nouns:
synset_max = get_greatest_synset_similarity_between(synset, noun)
if synset_max is not None:
count += 1
sim = WordnetHandler.cal_similarity(synset, synset_max)
if sim != None:
p += sim
if count != 0:
p = p/count
synsets_value.append(p)
return synsets_value
def get_definition_value_with_synsetwn(definition, synsets_wn):
synsets_value = []
# nouns = PreprocessDefinition.preprocess_sentence_to_nouns(definition)
nouns = PreprocessDefinition.preprocess_sentence(definition)
# nouns = list(set(nouns))
for synset in synsets_wn:
count = 0
p = 0
for noun in nouns:
synset_max = get_greatest_synset_similarity_between([synset], noun)
if synset_max is not None:
count += 1
sim = WordnetHandler.cal_similarity(synset, synset_max)
if sim != None:
p += sim
if count != 0:
p = p/count
synsets_value.append(p)
return synsets_value
