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.
This library is a C port of the implementation of Limited-memory
Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method written by Jorge
Nocedal. The original FORTRAN source code is available at:
http://www.ece.northwestern.edu/~nocedal/lbfgs.html
CRFSuite is an implementation of Conditional Random Fields (CRFs) for
labeling sequential data. The first priority of this software is to
train and use CRF models as fast as possible even at the expense of
its memory space and code generality. CRFsuite runs 5.4 - 61.8 times
faster than C++ implementations for training. CRFsuite supports
parameter estimation with L1 regularization (Laplacian prior) using
Orthant-Wise Limited-memory Quasi-Newton (OW-LQN) method and L2
regularization (Gaussian prior) using Limited-memory BFGS (L-BFGS)
method.