class Sentiment:
def __init__(self, modelfile=''):
self.Review = Review(modelfile)
def predict(self, Review, content):
print "content:", content
dic_content = json.loads(content)
s = dic_content['body']
bodyList = re.split(u';|；|,|，|。|\?|？|！|!', s)
bodyList = [i for i in bodyList if i != ""]
f_sentiment = []
for i in bodyList:
print i
f_sentiment.append(self.Review.predictPraise(i.strip()))
print "f_sentiment:", f_sentiment
length = len(bodyList)
f_position = []
for i in range(length):
cal = pow(float(i - length / 2), 2) / pow(length / 2, 2)
f_position.append(cal)
print "f_position:", f_position
#f_keyword = findKeyword(bodyList)
f = []
for i in range(length):
f.append(f_sentiment[i] * 0.6 + f_position[i] * 0.4)
#f = [i*0.6 for i in f_sentiment] + [i*0.4 for i in f_position]
print "f:", f
return max(f)
class PythonServiceServer:
def __init__(self):
self.Review = Review(reviewModel)
self.Sentiment = Sentiment(reviewModel)
#return positive(1), negative(-1) or neutral(0) sentiment
def getSentiment(self, content):
func = "getSentiment"
try:
res = self.Sentiment.predict(self.Review, str(content.strip()))
print res
except Exception as e:
logging.error("Error: host: %s \t func: %s \t content: %s \t ",
self.host, func, content)
res = 0
#logging.info("host: %s \t func: %s \t content: %s \t result: %s ",self.host, func, content, res)
return res
#return the degree various from 0 to 1 about bad review to good review
def getReview(self, content):
func = "getReview"
try:
content = "".join(content.split("\n"))
res = self.Review.predictPraise(str(content.strip()))
except Exception as e:
logging.error("Error: host: %s \t func: %s \t content: %s \t ",
self.host, func, content)
res = 0
#logging.info("host: %s \t func: %s \t content: %s \t result: %s ",self.host, func, content, res)
return res
class Sentiment:
def __init__(self, modelfile = ''):
self.Review = Review(modelfile)
def predict(self,Review, content):
print "content:",content
dic_content = json.loads(content)
s = dic_content['body']
bodyList = re.split(u';|；|,|，|。|\?|？|！|!', s)
bodyList = [i for i in bodyList if i != ""]
f_sentiment = []
for i in bodyList:
print i
f_sentiment.append(self.Review.predictPraise(i.strip()))
print "f_sentiment:", f_sentiment
length = len(bodyList)
f_position = []
for i in range(length):
cal = pow(float(i-length/2), 2)/pow(length/2, 2)
f_position.append(cal)
print "f_position:", f_position
#f_keyword = findKeyword(bodyList)
f = []
for i in range(length):
f.append(f_sentiment[i] * 0.6 + f_position[i] * 0.4)
#f = [i*0.6 for i in f_sentiment] + [i*0.4 for i in f_position]
print "f:", f
return max(f)
class PythonServiceServer:
def __init__(self):
self.Review = Review(reviewModel)
self.Sentiment = Sentiment(reviewModel)
#return positive(1), negative(-1) or neutral(0) sentiment
def getSentiment(self, content):
func = "getSentiment"
try:
res = self.Sentiment.predict(self.Review, str(content.strip()))
print res
except Exception as e:
logging.error("Error: host: %s \t func: %s \t content: %s \t ",self.host, func, content)
res = 0
#logging.info("host: %s \t func: %s \t content: %s \t result: %s ",self.host, func, content, res)
return res
#return the degree various from 0 to 1 about bad review to good review
def getReview(self, content):
func = "getReview"
try:
content = "".join(content.split("\n"))
res = self.Review.predictPraise(str(content.strip()))
except Exception as e:
logging.error("Error: host: %s \t func: %s \t content: %s \t ",self.host, func, content)
res = 0
#logging.info("host: %s \t func: %s \t content: %s \t result: %s ",self.host, func, content, res)
return res
def __init__(self):
self.Review = Review(reviewModel)
self.Sentiment = Sentiment(reviewModel)
def __init__(self, modelfile=''):
self.Review = Review(modelfile)
def __init__(self, modelfile = ''):
self.Review = Review(modelfile)
def __init__(self):
self.Review = Review(reviewModel)
self.Sentiment = Sentiment(reviewModel)