# row
arrRowDict = [];
arrRowDict.append("--");
for i in range(len(dict_words)):
if not dict_words[str(i)].has_key('tv'):
dict_words[str(i)]['tv'] = "--";
if dict_words[str(i)]['tv'] == None:
dict_words[str(i)]['tv'] = "--"
arrRowDict.append(dict_words[str(i)]["tv"].encode('utf8'));
FileProcess.write_to_excel_file("Results/"+WORD+"_synsets_synsets_nbest_withword_average_vn.csv",arrRowDict,matrix_similarity)
####################################################################################################
dictOxford = OxfordParser.readOxfordNouns();
print dictOxford
def similarityWordB():
for word in dictOxford:
print word
print dictOxford[word]
if word == 'bank':
similarity_by_synsets_synsets_nbest_withword_average(word,dictOxford[word]);
########################################
########################################
# row
for i in range(len(dict_words)):
if not dict_words[str(i)].has_key('tv'):
dict_words[str(i)]['tv'] = "--";
if dict_words[str(i)]['tv'] == None:
dict_words[str(i)]['tv'] = "--"
ox_word = dict_words[str(i)]["tv"].encode('utf8');
ox_words.append(ox_word)
for i in range(len(wn_words)):
wn_word = wn_words[i].name()
dict_wn_ox[wn_word] = []
indexs_max = get_best_max_index(matrix_similarity[i])
for index in indexs_max:
ox_word = ox_words[index]
dict_wn_ox[wn_word].append(ox_word)
return dict_wn_ox
__dict_ox_nouns__ = OxfordParser.readOxfordNouns();
def cal_similarity_for_word(word):
filted_dict = {}
if __dict_ox_nouns__.has_key(word):
if not (word is None or __dict_ox_nouns__[word] is None):
filted_dict = similarity_without_choice(word,__dict_ox_nouns__[word]);
return filted_dict
#cal_similarity_for_word("bank")
