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中文文本分析工具包(包括- 文本分类 - 文本聚类 - 文本相似性 - 关键词抽取 - 关键短语抽取 - 情感分析 - 文本纠错 - 文本摘要 - 主题关键词-同义词、近义词-事件三元组抽取)

License: Apache License 2.0

Python 100.00%
text-ana text-classification text-clustering text-similarity key-words sentiment-analysis spell-corrector text-summatizer event-extraction topic-keywords

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text_analysis_tools's Issues

用test_data试用kmeans/dbscan聚类模型时报错TypeError

weights = self.get_text_tfidf_matrix(corpus)
self.vectorizer.fit_transform(corpus)
File "D:\anaconda3\lib\site-packages\sklearn\feature_extraction\text.py", line 1225, in fit_transform
max_features)

File "D:\anaconda3\lib\site-packages\sklearn\feature_extraction\text.py", line 1095, in _limit_features
return X[:, kept_indices], removed_terms

File "D:\anaconda3\lib\site-packages\scipy\sparse_index.py", line 35, in getitem
row, col = self._validate_indices(key)

File "D:\anaconda3\lib\site-packages\scipy\sparse_index.py", line 148, in _validate_indices
col = self._asindices(col, N)

File "D:\anaconda3\lib\site-packages\scipy\sparse_index.py", line 169, in _asindices
max_indx = x.max()

**return umr_maximum(a, axis, None, out, keepdims, initial, where)

TypeError: int() argument must be a string, a bytes-like object or a number, not '_NoValueType'**

spell_correct.py代码有误,附纠错

92和93行代码应改为:

92 word_pinyin = self.p.get_pinyin(word, splitter=' ')
93 candidate_pinyin = self.candidates(word_pinyin.split(" "))

62行代码应改为:

62 return (self.known(word) or self.known(self.edits1(word)) or self.known(self.edits2(word)) or word)

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