Download JAR files tagged by efficient with all dependencies
rush from group edu.utah.bmi (version 1.0)
RuSH is an efficient, reliable, and easy adaptable rule-based sentence segmentation solution. It is
specifically designed to handle the telegraphic written text in clinical note. It leverages a nested hash table
to execute simultaneous rule processing, which reduces the impact of the rule-base growth on execution time and
eliminates the effect of rule order on accuracy.
If you wish to cite RuSH in a publication, please use:
Jianlin Shi ; Danielle Mowery ; Kristina M. Doing-Harris ; John F. Hurdle.RuSH: a Rule-based Segmentation Tool
Using Hashing for Extremely Accurate Sentence Segmentation of Clinical Text. AMIA Annu Symp Proc. 2016: 1587.
The full text can be found at:
https://knowledge.amia.org/amia-63300-1.3360278/t005-1.3362920/f005-1.3362921/2495498-1.3363244/2495498-1.3363247?timeStamp=1479743941616
Artifact rush
Group edu.utah.bmi
Version 1.0
Last update 23. April 2017
Organization The Department of Biomedical Informatics, University of Utah
URL https://github.com/jianlins/RuSH
License The Apache Software License, Version 2
Dependencies amount 6
Dependencies uimaj-core, uimaj-tools, uimaj-document-annotation, uimafit-core, uimaj-examples, junit,
There are maybe transitive dependencies!
Group edu.utah.bmi
Version 1.0
Last update 23. April 2017
Organization The Department of Biomedical Informatics, University of Utah
URL https://github.com/jianlins/RuSH
License The Apache Software License, Version 2
Dependencies amount 6
Dependencies uimaj-core, uimaj-tools, uimaj-document-annotation, uimafit-core, uimaj-examples, junit,
There are maybe transitive dependencies!
jburg from group net.sourceforge.jburg (version 1.10.3)
A bottom-up rewrite machine is a compiler construction tool that is often used in the compiler's back end to
convert a tree-structured representation of a program into machine code -- or, in Java's case, bytecode.
JBurg can also be used as a general-purpose dynamic programming engine. JBurg is descended from iburg-class
BURGs, described in Fraser, Hanson, and Proebsting's paper, "Engineering a Simple, Efficient Code Generator
Generator."
JBurg brings similar O(N) minimum-cost tree rewriting capabilities to Java, and also allows the programmer to
specify transitions between non-terminal states, that are significantly more powerful than iburg's transitive
closures: JBurg transformation rules allow the transformation to inject additional program logic, which makes
a JBurg specification more like a grammar than like a list of pattern-matching rules.
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Artifact jburg
Group net.sourceforge.jburg
Version 1.10.3
Last update 24. February 2016
Organization not specified
URL http://jburg.sourceforge.net/
License Common Public License Version 1.0
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
Group net.sourceforge.jburg
Version 1.10.3
Last update 24. February 2016
Organization not specified
URL http://jburg.sourceforge.net/
License Common Public License Version 1.0
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
jadex-rules-base from group org.activecomponents.jadex (version 4.0.267)
Jadex Rules is a small lightweight rule engine, which currently employs the well-known Rete algorithm for highly efficient rule matching. Jadex rules is therefore similar to other rule engines like JESS and Drools. Despite the similarities there are also important differences between these systems:
* Jadex Rules is very small and intended to be used as component of other software. Even though rules can be specified in a Java dialect as well as (a small variation of) the CLIPS language its primary usage is on the API level. Jadex Rules is currently the core component of the Jadex BDI reasoning engine.
* Jadex Rules cleanly separates between state and rule representation. This allows the state implementation as well as the matcher to be flexibly exchanged. Some experiments have e.g. been conducted with a Jena representation. Regarding the matcher, it is planned to support also the Treat algorithm, which has a lower memory footprint than Rete.
* Jadex Rules pays close attention to rule debugging. The state as well as the rete engine can be observed at runtime. The rule debugger provides functionalities to execute a rule program stepwise and also use rule breakpoints to stop the execution at those points.
Group: org.activecomponents.jadex Artifact: jadex-rules-base
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Show all versions Show documentation Show source
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Artifact jadex-rules-base
Group org.activecomponents.jadex
Version 4.0.267
Last update 08. September 2022
Organization not specified
URL https://www.activecomponents.org
License GPL-3.0
Dependencies amount 4
Dependencies jadex-util-commons, jadex-util-concurrent, jadex-serialization-xml, antlr-runtime,
There are maybe transitive dependencies!
Group org.activecomponents.jadex
Version 4.0.267
Last update 08. September 2022
Organization not specified
URL https://www.activecomponents.org
License GPL-3.0
Dependencies amount 4
Dependencies jadex-util-commons, jadex-util-concurrent, jadex-serialization-xml, antlr-runtime,
There are maybe transitive dependencies!
intelligentgraph from group com.inova8 (version 0.9.4)
The IntelligentGraph SAIL offers an extended capability for embedded calculation support within any RDF graph. When enabled as an RDF4J SAIL, it offers calculation functionality as part of the RDF4J engine, on top of any RDF4J repository, using a variety of script engines including JavaScript, Jython, and Groovy. It preserves the SPARQL capability of RDF4J, but with additional capabilities for calculation debugging and tracing.
IntelligentGraph includes the PathQL query language. Just as a spreadsheet cell calculation needs to access other cells, an IntelligentGraph calculation needs to access other nodes within the graph. Although full access to the underlying graph is available to any of the scripts, PathQL provides a succinct, and efficient method to access directly or indirectly related nodes. PathQL can either return just the contents of the referenced nodes, or the contents and the path to the referenced nodes.
PathQL can also be used standalone to query the IntelligentGraph-enabled RDF database. This supplements, rather than replaces, SPARQL and GraphQL, as it provides graph-path querying rather than graph-pattern querying capabilities to any IntelligentGraph-enabled RDF database.
The principles of IntelligentGraph are described here: https://inova8.com/bg_inova8.com/intelligent-graph-knowledge-graph-embedded-analysis/
The full PathQL syntax is described here: https://inova8.com/bg_inova8.com/pathpatternql-intelligently-finding-knowledge-as-a-path-through-a-maze-of-facts/
Using Jupyter as an IDE to IntelligentGraph and RDF4J, shown here: https://inova8.com/bg_inova8.com/intelligentgraph-getting-started/
IntelligentGraph source is here in GitHub: https://github.com/peterjohnlawrence/com.inova8.intelligentgraph
IntelligentGraph Docker containers are available here: https://hub.docker.com/repository/docker/inova8/intelligentgraph
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Artifact intelligentgraph
Group com.inova8
Version 0.9.4
Last update 26. April 2022
Organization inova8
URL https://www.inova8.com
License The Apache License, Version 2.0
Dependencies amount 6
Dependencies commons-cli, rdf4j-runtime, antlr4-runtime, seeq-sdk, jcl-over-slf4j, jericho-html,
There are maybe transitive dependencies!
Group com.inova8
Version 0.9.4
Last update 26. April 2022
Organization inova8
URL https://www.inova8.com
License The Apache License, Version 2.0
Dependencies amount 6
Dependencies commons-cli, rdf4j-runtime, antlr4-runtime, seeq-sdk, jcl-over-slf4j, jericho-html,
There are maybe transitive dependencies!
jadex-rules from group org.activecomponents.jadex (version 3.0.117)
Jadex Rules is a small lightweight rule engine, which currently employs the well-known Rete algorithm for highly efficient rule matching. Jadex rules is therefore similar to other rule engines like JESS and Drools. Despite the similarities there are also important differences between these systems:
* Jadex Rules is very small and intended to be used as component of other software. Even though rules can be specified in a Java dialect as well as (a small variation of) the CLIPS language its primary usage is on the API level. Jadex Rules is currently the core component of the Jadex BDI reasoning engine.
* Jadex Rules cleanly separates between state and rule representation. This allows the state implementation as well as the matcher to be flexibly exchanged. Some experiments have e.g. been conducted with a Jena representation. Regarding the matcher, it is planned to support also the Treat algorithm, which has a lower memory footprint than Rete.
* Jadex Rules pays close attention to rule debugging. The state as well as the rete engine can be observed at runtime. The rule debugger provides functionalities to execute a rule program stepwise and also use rule breakpoints to stop the execution at those points.
Group: org.activecomponents.jadex Artifact: jadex-rules
Show all versions Show documentation Show source
Show all versions Show documentation Show source
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Artifact jadex-rules
Group org.activecomponents.jadex
Version 3.0.117
Last update 10. May 2020
Organization not specified
URL https://www.activecomponents.org
License GPL-3.0
Dependencies amount 3
Dependencies jadex-commons, jadex-xml, antlr-runtime,
There are maybe transitive dependencies!
Group org.activecomponents.jadex
Version 3.0.117
Last update 10. May 2020
Organization not specified
URL https://www.activecomponents.org
License GPL-3.0
Dependencies amount 3
Dependencies jadex-commons, jadex-xml, antlr-runtime,
There are maybe transitive dependencies!
openimaj from group org.openimaj (version 1.3.10)
OpenIMAJ (Open Intelligent Multimedia in Java) is a collection of libraries and tools for multimedia analysis written in the Java programming language. OpenIMAJ intends to be the first truly complete multimedia analysis library and contains modules for analysing images, videos, text, audio and even webpages. The OpenIMAJ image and video analysis and feature extraction modules contain methods for processing visual content and extracting state-of-the-art features, including SIFT. The OpenIMAJ clustering and nearest-neighbour libraries contain efficient, multi-threaded implementations of clustering algorithms including Hierarchical K-Means and Approximate K-Means. The clustering library makes it possible to easily create visual-bag-of-words representations for images and video with very large vocabularies. The text-analysis modules contain implementations of a statistical language classifier and low-level processing pipeline. A number of modules deal with content creation, including interactive slideshows and animations. The hardware integration modules allow cross-platform integration with devices including webcams, the Microsoft Kinect, and even devices such as GPS's. OpenIMAJ also incorporates a number of tools to enable extremely-large-scale multimedia analysis using a distributed computing approach based on Apache Hadoop.
Group: org.openimaj Artifact: openimaj
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Artifact openimaj
Group org.openimaj
Version 1.3.10
Last update 09. February 2020
Organization The University of Southampton
URL http://www.openimaj.org
License New BSD
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
Group org.openimaj
Version 1.3.10
Last update 09. February 2020
Organization The University of Southampton
URL http://www.openimaj.org
License New BSD
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
jadex-rules from group net.sourceforge.jadex (version 2.4)
Jadex Rules is a small lightweight rule engine, which currently
employs the well-known Rete algorithm for highly efficient rule
matching. Jadex rules is therefore similar to other rule engines
like JESS and Drools. Despite the similarities there are also
important differences between these systems:
* Jadex Rules is very small and
intended to be used as component
of other software. Even though rules can be specified in a Java
dialect as well as (a small variation of) the CLIPS language
its primary usage is on the API level. Jadex Rules is currently
the core component of the Jadex BDI reasoning engine.
* Jadex Rules cleanly separates between state and rule representation.
This allows the state implementation as well as the matcher to be
flexibly exchanged. Some experiments have e.g. been conducted with
a Jena representation. Regarding the matcher, it is planned to
support also the Treat algorithm, which has a lower memory footprint
than Rete.
* Jadex Rules pays close attention to rule debugging. The state as
well as the rete engine can be observed at runtime. The rule debugger
provides functionalities to execute a rule program stepwise and also
use rule breakpoints to stop the execution at those points.
0 downloads
Artifact jadex-rules
Group net.sourceforge.jadex
Version 2.4
Last update 20. December 2013
Organization not specified
URL Not specified
License not specified
Dependencies amount 3
Dependencies jadex-commons, jadex-xml, antlr-runtime,
There are maybe transitive dependencies!
Group net.sourceforge.jadex
Version 2.4
Last update 20. December 2013
Organization not specified
URL Not specified
License not specified
Dependencies amount 3
Dependencies jadex-commons, jadex-xml, antlr-runtime,
There are maybe transitive dependencies!
adp from group de.cit-ec.tcs.alignment (version 3.1.1)
This module contains a more general approach to construct
AlignmentAlgorithms by relying on the theoretical concept of Algebraic
Dynamic Programming (ADP) as developed by Giegerich et al.
ADP defines four ingredients for an alignment algorithm:
1.) A signature that defines the permitted alignment operations.
Operations are just function templates with an associated arity, meaning
the number of arguments it takes from the left sequence and from the
right sequence.
In the TCSAlignmentToolbox we have a fixed signature with the following
operations:
REPLACEMENT(1, 1), DELETION(1, 0), INSERTION(0, 1), SKIPDELETION(1, 0)
and SKIPINSERTION(0, 1)
2.) A regular tree grammar that produces alignments, that is: sequences
of operations, in a restricted fashion.
3.) An algebra that can translate such trees to a cost. In the
TCSAlignmentToolbox this is a Comparator.
4.) A choice function, in case of the TCSAlignmentToolbox: the strict
minimum or the soft minimum.
An alignment algorithm in the TCSAlignmentToolbox sense of the word then
is the combination of choice function and grammar. While we provide
hardcoded versions of these combinations in the main package, the adp
package allows you to create your own grammars. You can combine them with
a choice function by instantiating one of the Algorithm classes provided
in this package with a grammar of your choice.
For example:
AlignmentAlgorithm algo = new SoftADPScoreAlgorithm(my_grammar, comparator);
creates an alignment algorithm that implicitly produces all possible
alignments your grammar can construct with the given input, translates them
to a cost using the algebra/comparator you provided and applies the
soft minimum to return the score. This all gets efficient by dynamic
programming.
Note that there is runtime overhead when using this method in comparison
with the hardcoded algorithms. But for complicated grammars this is a much
easier way to go.
For more information on the theory, please refer to my master's thesis:
"Adaptive Affine Sequence Alignment using Algebraic Dynamic Programming"
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Artifact adp
Group de.cit-ec.tcs.alignment
Version 3.1.1
Last update 26. October 2018
Organization not specified
URL http://openresearch.cit-ec.de/projects/tcs
License The GNU Affero General Public License, Version 3
Dependencies amount 1
Dependencies algorithms,
There are maybe transitive dependencies!
Group de.cit-ec.tcs.alignment
Version 3.1.1
Last update 26. October 2018
Organization not specified
URL http://openresearch.cit-ec.de/projects/tcs
License The GNU Affero General Public License, Version 3
Dependencies amount 1
Dependencies algorithms,
There are maybe transitive dependencies!
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