document[term[1]].append(term[2])
for key, item in document.items():
texts.append(item)
ids.append(key)
# create corpus and dictionary
dictionary = corpora.Dictionary(texts)
corpus = [dictionary.doc2bow(text) for text in texts]
# learn lda model
ldamodel = gensim.models.ldamodel.LdaModel(corpus,
num_topics=500,
id2word=dictionary,
passes=20)
#example
#print(ldamodel.print_topics(num_topics=20, num_words=7))
#lda = ldamodel[dictionary.doc2bow(texts[0])]
#print(lda[0][0])
#print(ldamodel.print_topic(lda[0][0]))
#print(texts[0])
dataHandler2 = DataHandler("localhost", dbUser, dbPw, "kisa")
#check document topic and related document by topic
for i in range(len(texts)):
lda = ldamodel[dictionary.doc2bow(texts[i])]
if lda:
dataHandler2.insertRelatedTopic(ids[i], str(lda[0][0]))
document[term[1]].append(term[2])
for key, item in document.items() :
texts.append(item)
ids.append(key)
# create corpus and dictionary
dictionary = corpora.Dictionary(texts)
corpus = [dictionary.doc2bow(text) for text in texts]
# learn lda model
ldamodel = gensim.models.ldamodel.LdaModel(corpus, num_topics=500, id2word = dictionary, passes=20)
#example
#print(ldamodel.print_topics(num_topics=20, num_words=7))
#lda = ldamodel[dictionary.doc2bow(texts[0])]
#print(lda[0][0])
#print(ldamodel.print_topic(lda[0][0]))
#print(texts[0])
dataHandler2 = DataHandler("localhost", dbUser, dbPw, "kisa")
#check document topic and related document by topic
for i in range(len(texts)):
lda = ldamodel[dictionary.doc2bow(texts[i])]
if lda :
dataHandler2.insertRelatedTopic(ids[i], str(lda[0][0]))
