Set LICENSE.
LibOFX 0.9.0:
- this release now exports version information thus allowing depending applications
to determine the version of LibOFX to compile against
- some fields have been added to OfxFiLogin to allow for modification of some
OFX header fields in outgoing requests. Together with the latest AqBanking3 this
should fix the problem with servers suddenly rejecting connections from LibOFX
applications
- the calling application can now tell libofx where the data files reside. This allows
for relocatable binaries (most importantly on Windows)
- some warnings from recent versions of GCC have been fixed
- libOFX can now easily be cross-compiled for Windows on Linux
- the OFX header is now scanned for a hint regarding the encoding of the document and
convert the data to UTF8 if iconv is available at compile time.
- the API for online requests has been cleaned up
* page.tmpl: Accidentially broke po plugin's otherlanguages list
styling when modifying for html5; now fixed.
* Fix a bug that prevented matching deleted comments, and so did
not update pages that had contained them.
GMediaServer is a UPnP compatible media server for the GNU system. It is part of
the GNU project.
GMediaServer serves audio and video files to certain network connected media
players. Most hardware media players only play music and/or video--they don't
provide the media themselves. Those media files have to come from a device on
the network. GMediaServer is a server for such UPnP compatible media players,
including:
* NETGEAR Wireless Digital Music Player (MP101)
* Linksys(R) Wireless-B Music System (WMLS11B)
* Linksys(R) Wireless-B Media Link for Music (WML11B)
* Philips Streamium SL300i
* Philips Streamium RC9800i
* Omnifi DMS1
* SMC EZ Stream 11Mbps Wireless Audio Adaptor (SMCWAA-B)
* D-Link DSM-520 Wireless HD Media Player
* Roku SoundBridge Network Music Player M1000
* Terratec NOXON 2 audio
Other UPnP media players (including software based) may work as well--see the
manual for a more complete list.
Changes:
* Patch for longtable takes package arydshln into account.
* Language definitions for \autoref are provided automatically
without global or package language options if babel is loaded
before.
* pdfencoding=auto: Escape TeX characters in .out file after
successful conversion to PDFDocEncoding (or subset).
* nameref 2.40: Support of environment `description'.
changes:
-Added surround channel mapping API and capability
-New config file options
-misc updates and fixes
pkgsrc note: The format structure passed to ao_open_*() has grown a new
member ("matrix", for channel mapping). All client pkgs need to be
checked that it is at least zero-initialized.
changes:
-improved kiosk use
-Yellow location for valid SSL, red for invalid
-UI improvements
-bugfixes
pkgsrc change: Drop Linux conditional for installation if the
adblock config file. It seems to depend on the shared library file
extension which might be different than .so on some platforms, but
it is just a config file which doesn't hurt if it is not found.
-install some "style" definitions
-use "gmake" as default make tool -- the build process depends
on gnumake's "-w" flag (can be adjusted in project properties, but this
way it works out of the box)
bump PKGREVISION
CaboCha is a Japanese dependency analysis machine based on Support Vector
Machines. It is (89.29%) system that accuracy is the highest as a statistical
Japanese dependency analysis machine as of June, 2001. Moreover, definite
analytical algorithm (Cascaded Chunking Model) that doesn't do back-track is
adopted, and an efficient analysis can be done comparatively.
This package is ruby module for CaboCha.
CaboCha is a Japanese dependency analysis machine based on Support Vector
Machines. It is (89.29%) system that accuracy is the highest as a statistical
Japanese dependency analysis machine as of June, 2001. Moreover, definite
analytical algorithm (Cascaded Chunking Model) that doesn't do back-track is
adopted, and an efficient analysis can be done comparatively.
This package is python module for CaboCha.
CaboCha is a Japanese dependency analysis machine based on Support Vector
Machines. It is (89.29%) system that accuracy is the highest as a statistical
Japanese dependency analysis machine as of June, 2001. Moreover, definite
analytical algorithm (Cascaded Chunking Model) that doesn't do back-track is
adopted, and an efficient analysis can be done comparatively.
This package is perl module for CaboCha.
CaboCha is a Japanese dependency analysis machine based on Support Vector
Machines. It is (89.29%) system that accuracy is the highest as a statistical
Japanese dependency analysis machine as of June, 2001. Moreover, definite
analytical algorithm (Cascaded Chunking Model) that doesn't do back-track is
adopted, and an efficient analysis can be done comparatively.
YamCha is a generic, customizable, and open source text chunker oriented toward
a lot of NLP tasks, such as POS tagging, Named Entity Recognition, base NP
chunking, and Text Chunking. YamCha is using a state-of-the-art machine learning
algorithm called Support Vector Machines (SVMs), first introduced by Vapnik in
1995.
This package is ruby module for YamCha.
YamCha is a generic, customizable, and open source text chunker oriented toward
a lot of NLP tasks, such as POS tagging, Named Entity Recognition, base NP
chunking, and Text Chunking. YamCha is using a state-of-the-art machine learning
algorithm called Support Vector Machines (SVMs), first introduced by Vapnik in
1995.
This package is python module for YamCha.
YamCha is a generic, customizable, and open source text chunker oriented toward
a lot of NLP tasks, such as POS tagging, Named Entity Recognition, base NP
chunking, and Text Chunking. YamCha is using a state-of-the-art machine learning
algorithm called Support Vector Machines (SVMs), first introduced by Vapnik in
1995.
This package is perl module for YamCha.
YamCha is a generic, customizable, and open source text chunker oriented toward
a lot of NLP tasks, such as POS tagging, Named Entity Recognition, base NP
chunking, and Text Chunking. YamCha is using a state-of-the-art machine learning
algorithm called Support Vector Machines (SVMs), first introduced by Vapnik in
1995.
YamCha is exactly the same system which performed the best in the CoNLL2000
Shared Task, Chunking and BaseNP Chunking task.
