# 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")