Gensim 在句子中查找主题

Question

我已经在语料库上训练了 LDA 算法，我想做的是为每个句子获取它对应的主题，以便在算法发现的内容和标签之间进行比较我有。

我试过下面的代码，但结果很糟糕我发现了很多主题17（可能是体积的25％，应该接近5％）

感谢您的帮助

# text lemmatized: list of string lemmatized
dico = Dictionary(texts_lemmatized)
corpus_lda = [dico.doc2bow(text) for text in texts_lemmatized]

lda_ = LdaModel(corpus_lda, num_topics=18)

df_ = pd.DataFrame([])
data = []

# theme_commentaire = label of the string
for i in range(0, len(theme_commentaire)):
     # lda_.get_document_topics() gives the distribution of all topic for a specific sentence
     algo = max(lda_.get_document_topics(corpus_lda[i]))[0]
     human = theme_commentaire[i]
     data.append([str(algo), human])

cols = ['algo', 'human']
df_ = pd.DataFrame(data, columns=cols)
df_.head()

Answer 1

已在评论中解决：

I've found my problem though, It's the max() function, it operates on the key value of my list of tuple [(num_topics, probability)] so basically I'll get 17 most of the time because it's the biggest key. – glouis

Gensim 在句子中查找主题

Gensim find topics in sentences

python

gensim