Path: csiph.com!aioe.org!bofh.it!news.nic.it!robomod From: Markus Koschany Newsgroups: linux.debian.bugs.dist,linux.debian.devel,linux.debian.maint.java Subject: Bug#986678: ITP: openrefine-arithcode -- Java implementation of arithmetic coding and PPM compression Date: Fri, 09 Apr 2021 13:30:02 +0200 Message-ID: X-Mailbox-Line: From debian-bugs-dist-request@lists.debian.org Fri Apr 9 11:24:09 2021 Old-Return-Path: X-Spam-Flag: NO X-Spam-Score: -4.2 Reply-To: Markus Koschany , 986678@bugs.debian.org Resent-To: debian-bugs-dist@lists.debian.org Resent-Cc: debian-devel@lists.debian.org, debian-java@lists.debian.org, apo@debian.org, wnpp@debian.org X-Debian-Pr-Message: report 986678 X-Debian-Pr-Package: wnpp X-Spam-Bayes: score:0.0000 Tokens: new, 17; hammy, 148; neutral, 36; spammy, 2. spammytokens:0.970-+--models, 0.948-+--H*r:bugs.debian.org hammytokens:0.000-+--X-Debbugs-Cc, 0.000-+--XDebbugsCc, 0.000-+--H*M:reportbug, 0.000-+--H*MI:reportbug, 0.000-+--H*x:reportbug Content-Type: text/plain; charset="us-ascii" MIME-Version: 1.0 Content-Transfer-Encoding: 7bit X-Mailer: reportbug 7.10.3 X-Debian-Message: from BTS X-Mailing-List: archive/latest/1659727 List-ID: List-URL: Approved: robomod@news.nic.it Lines: 20 Organization: linux.* mail to news gateway Sender: robomod@news.nic.it X-Original-Date: Fri, 09 Apr 2021 13:21:26 +0200 X-Original-Message-ID: <161796728631.29490.14345277148546128649.reportbug@spike> Xref: csiph.com linux.debian.bugs.dist:1055213 linux.debian.devel:100069 linux.debian.maint.java:12127 Package: wnpp Severity: wishlist Owner: Markus Koschany X-Debbugs-Cc: debian-devel@lists.debian.org, debian-java@lists.debian.org, apo@debian.org * Package name : openrefine-arithcode Version : 1.2 Upstream Author : Bob Carpenter * URL : https://github.com/bob-carpenter/java-arithcode * License : BSD-3-clause Programming Lang: Java Description : Java implementation of arithmetic coding and PPM compression Arithmetic coding is a general technique for coding the outcome of a stochastic process based on an adaptive model. The expected bit rate is the cross-entropy rate of the model versus the actual process. PPM, prediction by partial matching, is an adaptive statistical model of a symbol sequence which models the likelihood of the next byte based on a (relatively short) suffix of the sequence of previous bytes.