LibShortText: A Library for Short-text Classification and Analysis

Machine Learning Group at National Taiwan University
Contributors

Version 1.1 released on September 10, 2013.

Introduction

LibShortText is an open source tool for short-text classification and 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.

Download

The package includes the source code in Python and C/C++.

Please read the COPYRIGHT notice before using LibShortText. 

Documentation

H.-F. Yu, C.-H. Ho, Y.-C. Juan, and C.-J. Lin. LibShortText: A Library for Short-text Classification and Analysis

See README in the package for the practical use.

For developers, see Please check online documents for detailed usage.