def testNearbyWords(self): thu1 = thulac.thulac() #默认模式 text = thu1.cut("人脸识别", text=True) #进行一句话分词 words, tags = [], [] data = [x.rsplit('_', 1) for x in text.split()] for _ in data: assert len(_) == 2, "seg len should be 2" words.append(_[0]) tags.append(_[1]) for (k, v) in enumerate(tags): if v.startswith("n") or v.startswith("v"): # 去停,去标,去副词、形容词、代词 etc. synonyms.display( words[k]) # synonyms.display calls synonyms.nearby
def test_badcase_1(self): synonyms.display("人脸") # synonyms.display calls synonyms.nearby
def test_nearby(self): synonyms.display("奥运") # synonyms.display calls synonyms.nearby synonyms.display("北新桥") # synonyms.display calls synonyms.nearby
def cPrintDisplay(str): print('@+@') synonyms.display(str) print('@-@')
data_long = np.loadtxt("data_test1.csv",str,delimiter=",", skiprows=1) data_long ("国际劳工组织") cixing=[] for i in range(0,len(data_long)): cixing.append(synonyms.seg(data_long[i])) test=synonyms.nearby("人脸") test[0] print("识别: %s" % (synonyms.nearby("识别"))) print("NOT_EXIST: %s" % (synonyms.nearby("NOT_EXIST"))) synonyms.display("金融") synonyms.v() print(1) cixiangliang=[] for i in range(0,len(data_long)): try: cixiangliang.append(synonyms.v (data_long[i])) except: cixiangliang.append(-1) ciqinggan=[] for i in range(0,len(data_long)):
def test_nearby(self): synonyms.display("人脸") # synonyms.display calls synonyms.nearby
def testNearbyWords(self): synonyms.display("人脸") # synonyms.display calls synonyms.nearby
import synonyms synonyms.display("你好")
def testWordExit(wordexit): # 测试synonyms中是否存在这个词 synonyms.display(wordexit)
#!/usr/bin/env python #coding:utf-8 import synonyms # 获取近义词 print synonyms.nearby("计算机科学") # 输出近义词(display调用了synonyms的nearby方法) synonyms.display("计算机技术") # 获取两个词语或句子的相似度 print synonyms.compare("计算机科学", "计算机技术")
import synonyms print("人脸: %s" % (synonyms.nearby("人脸"))) print("识别: %s" % (synonyms.nearby("识别"))) print("NOT_EXIST: %s" % (synonyms.nearby("NOT_EXIST"))) print("=" * 50) sen1 = "发生历史性变革" sen2 = "发生历史性变革" r = synonyms.compare(sen1, sen2, seg=True) print("发生历史性变革 vs 发生历史性变革:", r) print("=" * 50) synonyms.display("飞机")
def test_nearby(self): synonyms.display("人脸") # synonyms.display calls synonyms.nearby
:param sen1: the original sentence :param sen2: the mutated sentence :param threshold: how much the two sentence are likely is okay :return: True for the two sentence are similar, false for not """ score = synonyms.compare(sen1, sen2) return False if score <= threshold else True # @online{Synonyms:hain2017, # author = {Hai Liang Wang, Hu Ying Xi}, # title = {中文近义词工具包Synonyms}, # year = 2017, # url = {https://github.com/huyingxi/Synonyms}, # urldate = {2017-09-27} # } if __name__ == "__main__": print(synonyms.display("今天")) print(synonyms.display("天气")) print(synonyms.display("真好")) print(synonyms.display("做")) print(synonyms.display("作业")) print(synonyms.display("喜欢")) print(synonyms.display("故事")) print(synonyms.display("猫")) print(synonyms.display("可爱")) print(synonyms.display("一种")) print(synonyms.display("动物")) print(synonyms.display("今天天气"))