16af52c1ec
analysis. It can handle the classification of, for example, titles,
questions, sentences, and short messages. Main features of
LibShortText include
* It is more efficient than general text-mining packages. On a
typical computer, processing and training 10 million short texts
takes only around half an hour.
* The fast training and testing is built upon the linear classifier
* LIBLINEAR
* Default options often work well without tedious tuning.
* An interactive tool for error analysis is included. Based on the
property that each short text contains few words, LibShortText
provides details in predicting each text.
12 lines
710 B
Text
12 lines
710 B
Text
LibShortText is an open source tool for short-text classification and
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analysis. It can handle the classification of, for example, titles,
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questions, sentences, and short messages. Main features of
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LibShortText include
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* It is more efficient than general text-mining packages. On a
|
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typical computer, processing and training 10 million short texts
|
|
takes only around half an hour.
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* The fast training and testing is built upon the linear classifier LIBLINEAR
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* Default options often work well without tedious tuning.
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* An interactive tool for error analysis is included. Based on the
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property that each short text contains few words, LibShortText
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|
provides details in predicting each text.
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