class BosonNlpp: def __init__(self): self.bonlp = BosonNLP('IKBIoANy.14545.A7GCYBnT9jIB') #情感分析 def testSentiment(self, s): result = self.bonlp.sentiment(s) return result #print(result) #命名实体识别 def lexicalAnalysis(self, s): result = self.bonlp.ner(s)[0] return result #依存文法分析 def textDependency(self, s): result = self.bonlp.depparser(s) return result #关键词提取 def testKeywords(self, s): result = self.bonlp.extract_keywords(s, top_k=10) return result #新闻分类 def textClassify(self, s): resultlist = self.bonlp.classify(s) classifys = { 0: '体育', 1: '教育', 2: '财经', 3: '社会', 4: '娱乐', 5: '军事', 6: '国内', 7: '科技', 8: '互联网', 9: '房产', 10: '国际', 11: '女人', 12: '汽车', 13: '游戏' } return (classifys[resultlist[0]]) #语义联想 def lexicalSynonym(self, term): result = self.bonlp.suggest(term, top_k=10) return result #分词与词性标注 def fenci(self, s): result = self.bonlp.tag(s) return result def newssubstract(self, s): #s=s.encode('utf8') s = s.decode('utf-8') result = self.bonlp.summary('', s) return result