def frp_multi(fr):
zz = fr['reviews']
multi_list = []
for yy in zz:
xx = yy['summary']
multi_list.append(xx)
abc = SentimentAnalysis()
list_tds = []
list_qc = []
list_c = []
list_dict = []
for ss in multi_list:
ss_a = list(jieba.cut(ss, cut_all=False))
ss_b = " ".join(ss_a)
#print (ss_b)
result = abc.analyze(ss_b)
#print (result)
for item in result:
t = item[0]
d = item[1]
s = item[4]
tds = [t, d, s]
list_tds.append(tds)
for tri in list_tds:
if tri not in list_qc:
list_qc.append(tri)
tri_count = list_tds.count(tri)
list_c.append(tri_count)
for ww in list_qc:
vc_index = list_qc.index(ww)
vc = list_c[vc_index]
vt = ww[0]
vd = ww[1]
vs = ww[2]
dict_a = {"对象": vt, "评价极性": vs, "描述词": vd, "评论数": vc}
list_dict.append(dict_a)
df = pd.DataFrame(list_dict, columns=["对象", "评价极性", "描述词", "评论数"])
df.to_csv("./ndetails.csv", index=False)
def frp_single(sentence):
abc = SentimentAnalysis()
result = abc.analyze(sentence)
str_a = []
jsonlist_a = []
for item in result:
aspect = item[0]
opinion = item[1]
relation = item[4]
#t = ***
a = {'target': aspect, 'description': opinion, 'sentiment': relation}
str_a.append(a)
for i in str_a:
json_info = json.dumps(i, default=set_default, ensure_ascii=False)
jsonlist_a.append(json_info)
return jsonlist_a
from preprocess import WordSet, WordEmbedding, KnowledgeBase
from sentiment_analysis import SentimentAnalysis
#sentence = '外观 漂亮'
#sentence = '外观 不 太 漂亮'
#sentence = '高 规格 的 用料 和 精致 的 做工'
#sentence = '炫酷 的 造型 、 充沛 的 动力 再 加上 本田 家族 运动 基因 的 传承'
parser = argparse.ArgumentParser()
parser.add_argument('-s', required=True)
args = parser.parse_args()
sentence = args.s
abc = SentimentAnalysis()
result = abc.analyze(sentence)
print('--------------------')
print('%s\n' % (sentence))
for item in result:
aspect = item[0]
opinion = item[1]
relation = item[4]
print('%s\t%s\t%s' % (aspect, opinion, relation))
print('--------------------')
for item in result:
aspect = item[0]
opinion = item[1]
relation = item[4]
knowledge = item[5]