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− | ==Problem An Solve== | + | ==Problem And Solve== |
− | ==Document classification of Sougou data ==
| + | *[[How to import the sparse data of vsm to weka]] |
− | * DATA
| + | |
− | :* Data from SougouLab [http://www.sogou.com/labs/dl/c.html],using SogouC.reduced(30M)
| + | |
− | :* 9-Classes:财经,IT,健康,体育,旅游,教育,招聘,文化,军事
| + | |
− | :* train and test: train(),test(),dev()
| + | |
− | *Text preprocessing
| + | |
− | :* Segment word using wordlist of 9W.(tencent)
| + | |
− | :* Remove stop word.stop_wordlist is
| + | |
− | :*
| + | |
− | *Some Tools
| + | |
− | :* weka
| + | |
− | :* scw
| + | |
− | :* google word2ve
| + | |
− | :* LDA
| + | |
− | ===VSM Test===
| + | |
− | *Data
| + | |
− | :* dimension:9402
| + | |
− | *Method
| + | |
− | :* document reprenstion: use the tf-idf weight for word weight
| + | |
− | :* classifier: Native Bayes
| + | |
− | *Result
| + | |
| | | |
− | ===LDA Test=== | + | ==Test== |
− | ===Word2vec Test===
| + | [[Sougou data]] |