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./wip/libshorttext, Library for short-text classification and analysis

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Branch: CURRENT, Version: 1.1, Package name: libshorttext-1.1, Maintainer: cheusov

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.

Required to run:
[lang/python27] [math/libsvm] [math/liblinear]

Master sites:

http://www.csie.ntu.edu.tw/~cjlin/libshorttext/ (Download)

SHA1: 2d9705195682fa1f25de30bd66711685f974a8c0
RMD160: 569d2f2a64f8fc311766b08cbef7086e1340ce55
Filesize: 798.608 KB

Version history: (Expand)

(2014-10-30) Package deleted from pkgsrc
(2014-10-20) Package added to pkgsrc.se, version libshorttext-1.1 (created)

CVS history: (Expand)

2014-10-29 18:13:28 by Aleksey Cheusov | Files touched by this commit (5) | Package removed

Log message:
Remove libshorttext (imported to pkgsrc)

2014-10-19 19:03:02 by Aleksey Cheusov | Files touched by this commit (5)

Log message:
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.