class Morph :
def __init__(self, nlpEngine = "Mecab"):
'''e
원하는 형태소 분석기 엔진으로 형태소 분석기 생성
:param nlpEngine: 형태소 분석기 이름(첫글자 대문자) str
'''
self.nlpEngine = nlpEngine
if nlpEngine == "Okt":
self.nlp = Okt()
elif nlpEngine == "Komoran":
self.nlp = Komoran()
elif nlpEngine == "Kkma":
self.nlp = Kkma()
elif nlpEngine == "Hannanum":
self.nlp = Hannanum()
elif nlpEngine == "Mecab":
self.nlp = Mecab()
elif nlpEngine == "Twitter":
self.nlp = Twitter()
else:
raise NameError("unknown nlp name")
def get_morphs(self, sentence, norm=True, stem=True, join=False):
if self.nlpEngine == "Mecab":
try :
a = self.nlp.parse(sentence)
b = [aa.split(',') for aa in a.split('\n')][:-2]
if stem :
s = [[d[3],d[0].split('\t')[1]] for d in b]
else :
s = [d[0].split('\t') for d in b]
if join :
j = ['/'.join(ss) for ss in s]
else :
j = [tuple(ss) for ss in s]
return j
except :
return []
else :
return self.nlp.pos(sentence, norm=norm, stem=stem, join=join)
def get_nouns(self,text):
if self.nlpEngine == "Mecab" :
all_tags_raw1 = self.nlp.parse(text).split("\n")
all_tags_raw2 = [tt.split(",")[0] for tt in all_tags_raw1]
all_tags = [t.split("\t") for t in all_tags_raw2]
nounList = []
for tags in all_tags :
if len(tags) == 2 :
if tags[1][0:2] in ['NN','NP'] :
nounList.append(tags[0])
print(nounList)
return nounList
else :
return self.nlp.nouns(text)
def get_nouns(self,text):
if self.nlpEngine == "Mecab" :
all_tags_raw1 = self.nlp.parse(text).split("\n")
all_tags_raw2 = [tt.split(",")[0] for tt in all_tags_raw1]
all_tags = [t.split("\t") for t in all_tags_raw2]
nounList = []
for tags in all_tags :
if len(tags) == 2 :
if tags[1][0:2] in ['NN','NP'] :
nounList.append(tags[0])
print(nounList)
return nounList
else :
return self.nlp.nouns(text)
