def getLabeledHudongItem(self, filename): labels = readCSV2(filename) List = [] i = 0 for line in labels: ctx = self.graph.find_one(label="HudongItem",property_key="title",property_value=line[0]) if ctx == None: continue; cur = HudongItem(ctx) cur.label = line[1] List.append(cur) print('load LabeledHudongItem over ...') return List
def create_predict(HudongItem_csv): # 读取neo4j内容 db = Neo4j() db.connectDB() predict_List = readCSVbyColumn(HudongItem_csv, 'title') file_object = open('vector.txt', 'a') model = FastText('wiki.zh.bin') count = 0 vis = set() for p in predict_List: cur = HudongItem(db.matchHudongItembyTitle(p)) count += 1 title = cur.title if title in vis: continue vis.add(title) wv_list = model[title] strr = str(title) print('===============') print(strr) for p in wv_list: strr += ' ' + str(p)[:7] print('===============') print(strr) print('===============') file_object.write(strr + "\n") print(str(count) + ' / ' + str(len(predict_List))) file_object.close()
def create_predict(HudongItem_csv): # 读取neo4j内容 db = Neo4j() db.connectDB() data_set = db.getLabeledHudongItem('labels.txt') classifier = Classifier('wiki.zh.bin') classifier.load_trainSet(data_set) classifier.set_parameter(weight=[1.0, 3.0, 0.2, 4.0, 0],k=10) predict_List = readCSVbyColumn(HudongItem_csv, 'title') file_object = open('predict_labels2.txt','a') count = 0 vis = set() for p in predict_List: cur = HudongItem(db.matchHudongItembyTitle(p)) if count > 200: break count += 1 if count <140 : continue title = cur.title if title in vis: continue vis.add(title) label = classifier.KNN_predict(cur) print(str(title)+" "+str(label)+": "+str(count)+"/"+str(len(predict_List))) file_object.write(str(title)+" "+str(label)+"\n") file_object.close()
def getAllHudongItem(self, limitnum): List = [] ge = self.graph.find(label="HudongItem", limit=limitnum) for g in ge: List.append(HudongItem(g)) print('load AllHudongItem over ...') return List
def getAllHudongItem(self, limitnum): List = [] matcher = NodeMatcher(self.graph) ge = matcher.match("hudongItem").limit(limitnum) #ge = self.graph.find(label="HudongItem", limit=limitnum) for g in ge: List.append(HudongItem(g)) print('load AllHudongItem over ...') return List
def getAllHudongItem(self, limitnum): List = [] ge = self.graph.find(label="HudongItem", limit=limitnum) for g in ge: List.append(HudongItem(g)) print('load AllHudongItem over ...') return List #test = Neo4j() #test.connectDB() #a = test.getLabeledHudongItem('labels.txt') #print(a[10].openTypeList)
def getAllHudongItem(self, limitnum): List = [] ge = self.graph.find(label="HudongItem", limit=limitnum) for g in ge: List.append(HudongItem(g)) print('load AllHudongItem over ...') return List #test = Neo4j() #test.connectDB() #answer = test.graph.find_one(label="HudongItem",property_key="title",property_value='火龙果') #print(answer) #a = test.getLabeledHudongItem('labels.txt') #print(a[10].openTypeList)