Download JAR files tagged by algorithms with all dependencies
toolbox-utils from group de.uni_leipzig.asv.toolbox (version 1.0)
ASV Toolbox is a modular collection of tools for the exploration of written language data. They work either on word lists or text and solve several linguistic classification and clustering tasks. The topics covered contain language detection, POS-tagging, base form reduction, named entity recognition, and terminology extraction. On a more abstract level, the algorithms deal with various kinds of word similarity, using pattern based and statistical approaches. The collection can be used to work on large real world data sets as well as for studying the underlying algorithms. The ASV Toolbox can work on plain text files and connect to a MySQL database. While it is especially designed to work with corpora of the Leipzig Corpora Collection, it can easily be adapted to other sources.
Artifact toolbox-utils
Group de.uni_leipzig.asv.toolbox
Version 1.0
Last update 13. August 2013
Organization not specified
URL http://wortschatz.uni-leipzig.de/~cbiemann/software/toolbox/
License MIT License
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
Group de.uni_leipzig.asv.toolbox
Version 1.0
Last update 13. August 2013
Organization not specified
URL http://wortschatz.uni-leipzig.de/~cbiemann/software/toolbox/
License MIT License
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
boilerpipe from group de.l3s.boilerpipe (version 1.1.0)
The boilerpipe library provides algorithms to detect and remove the surplus "clutter" (boilerplate, templates) around the main textual content of a web page.
The library already provides specific strategies for common tasks (for example: news article extraction) and may also be easily extended for individual problem settings.
Extracting content is very fast (milliseconds), just needs the input document (no global or site-level information required) and is usually quite accurate.
Boilerpipe is a Java library written by Christian Kohlschütter. It is released under the Apache License 2.0.
The algorithms used by the library are based on (and extending) some concepts of the paper "Boilerplate Detection using Shallow Text Features" by Christian Kohlschütter et al., presented at WSDM 2010 -- The Third ACM International Conference on Web Search and Data Mining New York City, NY USA.
10 downloads
Artifact boilerpipe
Group de.l3s.boilerpipe
Version 1.1.0
Last update 03. November 2010
Organization not specified
URL http://code.google.com/p/boilerpipe/
License Apache License 2.0
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
Group de.l3s.boilerpipe
Version 1.1.0
Last update 03. November 2010
Organization not specified
URL http://code.google.com/p/boilerpipe/
License Apache License 2.0
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
jung-parent from group io.github.devlibx.jung (version 3.1)
JUNG the Java Universal Network/Graph Framework--is a software
library that provides a common and extensible language for the
modeling, analysis, and visualization of data that can be
represented as a graph or network. It is written in Java, which
allows JUNG-based applications to make use of the extensive
built-in capabilities of the Java API, as well as those of other
existing third-party Java libraries. The JUNG architecture is
designed to support a variety of representations of entities and
their relations, such as directed and undirected graphs,
multi-modal graphs, graphs with parallel edges, and hypergraphs.
It provides a mechanism for annotating graphs, entities, and
relations with metadata. This facilitates the creation of
analytic tools for complex data sets that can examine the
relations between entities as well as the metadata attached to
each entity and relation. The current distribution of JUNG
includes implementations of a number of algorithms from graph
theory, data mining, and social network analysis, such as
routines for clustering, decomposition, optimization, random
graph generation, statistical analysis, and calculation of
network distances, flows, and importance measures (centrality,
PageRank, HITS, etc.). JUNG also provides a visualization
framework that makes it easy to construct tools for the
interactive exploration of network data. Users can use one of
the layout algorithms provided, or use the framework to create
their own custom layouts. In addition, filtering mechanisms are
provided which allow users to focus their attention, or their
algorithms, on specific portions of the graph.
Group: io.github.devlibx.jung Artifact: jung-parent
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Artifact jung-parent
Group io.github.devlibx.jung
Version 3.1
Last update 22. April 2021
Organization not specified
URL http://devlibx.github.io/jung/
License The BSD License
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
Group io.github.devlibx.jung
Version 3.1
Last update 22. April 2021
Organization not specified
URL http://devlibx.github.io/jung/
License The BSD License
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
jung-parent from group com.northdata.jung (version 2.2.0)
JUNG the Java Universal Network/Graph Framework--is a software
library that provides a common and extendible language for the
modeling, analysis, and visualization of data that can be
represented as a graph or network. It is written in Java, which
allows JUNG-based applications to make use of the extensive
built-in capabilities of the Java API, as well as those of other
existing third-party Java libraries. The JUNG architecture is
designed to support a variety of representations of entities and
their relations, such as directed and undirected graphs,
multi-modal graphs, graphs with parallel edges, and hypergraphs.
It provides a mechanism for annotating graphs, entities, and
relations with metadata. This facilitates the creation of
analytic tools for complex data sets that can examine the
relations between entities as well as the metadata attached to
each entity and relation. The current distribution of JUNG
includes implementations of a number of algorithms from graph
theory, data mining, and social network analysis, such as
routines for clustering, decomposition, optimization, random
graph generation, statistical analysis, and calculation of
network distances, flows, and importance measures (centrality,
PageRank, HITS, etc.). JUNG also provides a visualization
framework that makes it easy to construct tools for the
interactive exploration of network data. Users can use one of
the layout algorithms provided, or use the framework to create
their own custom layouts. In addition, filtering mechanisms are
provided which allow users to focus their attention, or their
algorithms, on specific portions of the graph.
Group: com.northdata.jung Artifact: jung-parent
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Artifact jung-parent
Group com.northdata.jung
Version 2.2.0
Last update 18. September 2020
Organization not specified
URL http://jrtom.github.io/jung/
License The BSD License
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
Group com.northdata.jung
Version 2.2.0
Last update 18. September 2020
Organization not specified
URL http://jrtom.github.io/jung/
License The BSD License
Dependencies amount 0
Dependencies No dependencies
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!
jung-parent from group net.sf.jung (version 2.1.1)
JUNG the Java Universal Network/Graph Framework--is a software
library that provides a common and extendible language for the
modeling, analysis, and visualization of data that can be
represented as a graph or network. It is written in Java, which
allows JUNG-based applications to make use of the extensive
built-in capabilities of the Java API, as well as those of other
existing third-party Java libraries. The JUNG architecture is
designed to support a variety of representations of entities and
their relations, such as directed and undirected graphs,
multi-modal graphs, graphs with parallel edges, and hypergraphs.
It provides a mechanism for annotating graphs, entities, and
relations with metadata. This facilitates the creation of
analytic tools for complex data sets that can examine the
relations between entities as well as the metadata attached to
each entity and relation. The current distribution of JUNG
includes implementations of a number of algorithms from graph
theory, data mining, and social network analysis, such as
routines for clustering, decomposition, optimization, random
graph generation, statistical analysis, and calculation of
network distances, flows, and importance measures (centrality,
PageRank, HITS, etc.). JUNG also provides a visualization
framework that makes it easy to construct tools for the
interactive exploration of network data. Users can use one of
the layout algorithms provided, or use the framework to create
their own custom layouts. In addition, filtering mechanisms are
provided which allow users to focus their attention, or their
algorithms, on specific portions of the graph.
Group: net.sf.jung Artifact: jung-parent
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Artifact jung-parent
Group net.sf.jung
Version 2.1.1
Last update 07. September 2016
Organization not specified
URL http://jrtom.github.io/jung/
License The BSD License
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
Group net.sf.jung
Version 2.1.1
Last update 07. September 2016
Organization not specified
URL http://jrtom.github.io/jung/
License The BSD License
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
jung2 from group net.sf.jung (version 2.0.1)
JUNG the Java Universal Network/Graph Framework--is a software
library that provides a common and extendible language for the
modeling, analysis, and visualization of data that can be
represented as a graph or network. It is written in Java, which
allows JUNG-based applications to make use of the extensive
built-in capabilities of the Java API, as well as those of other
existing third-party Java libraries. The JUNG architecture is
designed to support a variety of representations of entities and
their relations, such as directed and undirected graphs,
multi-modal graphs, graphs with parallel edges, and hypergraphs.
It provides a mechanism for annotating graphs, entities, and
relations with metadata. This facilitates the creation of
analytic tools for complex data sets that can examine the
relations between entities as well as the metadata attached to
each entity and relation. The current distribution of JUNG
includes implementations of a number of algorithms from graph
theory, data mining, and social network analysis, such as
routines for clustering, decomposition, optimization, random
graph generation, statistical analysis, and calculation of
network distances, flows, and importance measures (centrality,
PageRank, HITS, etc.). JUNG also provides a visualization
framework that makes it easy to construct tools for the
interactive exploration of network data. Users can use one of
the layout algorithms provided, or use the framework to create
their own custom layouts. In addition, filtering mechanisms are
provided which allow users to focus their attention, or their
algorithms, on specific portions of the graph.
Group: net.sf.jung Artifact: jung2
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Artifact jung2
Group net.sf.jung
Version 2.0.1
Last update 24. January 2010
Organization not specified
URL http://jung.sourceforge.net/site
License The BSD License
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
Group net.sf.jung
Version 2.0.1
Last update 24. January 2010
Organization not specified
URL http://jung.sourceforge.net/site
License The BSD License
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
chips-n-salsa from group org.cicirello (version 6.4.0)
Chips-n-Salsa is a Java library of customizable,
hybridizable, iterative, parallel, stochastic, and self-adaptive
local search algorithms. The library includes implementations of
several stochastic local search algorithms, including simulated
annealing, hill climbers, as well as constructive search algorithms
such as stochastic sampling. Chips-n-Salsa now also includes genetic
algorithms as well as evolutionary algorithms more generally. The
library very extensively supports simulated annealing. It includes
several classes for representing solutions to a variety of optimization
problems. For example, the library includes a BitVector class that
implements vectors of bits, as well as classes for representing
solutions to problems where we are searching for an optimal vector
of integers or reals. For each of the built-in representations, the
library provides the most common mutation operators for generating
random neighbors of candidate solutions, as well as common crossover
operators for use with evolutionary algorithms. Additionally, the
library provides extensive support for permutation optimization
problems, including implementations of many different mutation
operators for permutations, and utilizing the efficiently implemented
Permutation class of the JavaPermutationTools (JPT) library.
Chips-n-Salsa is customizable, making extensive use of Java's generic
types, enabling using the library to optimize other types of representations
beyond what is provided in the library. It is hybridizable, providing
support for integrating multiple forms of local search (e.g., using a hill
climber on a solution generated by simulated annealing), creating hybrid
mutation operators (e.g., local search using multiple mutation operators),
as well as support for running more than one type of search for the same
problem concurrently using multiple threads as a form of algorithm portfolio.
Chips-n-Salsa is iterative, with support for multistart metaheuristics,
including implementations of several restart schedules for varying the run
lengths across the restarts. It also supports parallel execution of multiple
instances of the same, or different, stochastic local search algorithms for
an instance of a problem to accelerate the search process. The library
supports self-adaptive search in a variety of ways, such as including
implementations of adaptive annealing schedules for simulated annealing,
such as the Modified Lam schedule, implementations of the simpler annealing
schedules but which self-tune the initial temperature and other parameters,
and restart schedules that adapt to run length.
0 downloads
Artifact chips-n-salsa
Group org.cicirello
Version 6.4.0
Last update 28. July 2023
Organization Cicirello.Org
URL https://chips-n-salsa.cicirello.org/
License GPL-3.0-or-later
Dependencies amount 3
Dependencies jpt, rho-mu, core,
There are maybe transitive dependencies!
Group org.cicirello
Version 6.4.0
Last update 28. July 2023
Organization Cicirello.Org
URL https://chips-n-salsa.cicirello.org/
License GPL-3.0-or-later
Dependencies amount 3
Dependencies jpt, rho-mu, core,
There are maybe transitive dependencies!
commons-crypto from group org.apache.commons (version 1.2.0)
Apache Commons Crypto is a cryptographic library optimized with AES-NI (Advanced Encryption
Standard New Instructions). It provides Java API for both cipher level and Java stream level.
Developers can use it to implement high performance AES encryption/decryption with the minimum
code and effort. Please note that Crypto doesn't implement the cryptographic algorithm such as
AES directly. It wraps to OpenSSL or JCE which implement the algorithms.
Features
--------
1. Cipher API for low level cryptographic operations.
2. Java stream API (CryptoInputStream/CryptoOutputStream) for high level stream encryption/decryption.
3. Both optimized with high performance AES encryption/decryption. (1400 MB/s - 1700 MB/s throughput in modern Xeon processors).
4. JNI-based implementation to achieve comparable performance to the native C/C++ version based on OpenSsl.
5. Portable across various operating systems (currently only Linux/MacOSX/Windows);
Apache Commons Crypto loads the library according to your machine environment (it checks system properties, `os.name` and `os.arch`).
6. Simple usage. Add the commons-crypto-(version).jar file to your classpath.
Export restrictions
-------------------
This distribution includes cryptographic software.
The country in which you currently reside may have restrictions
on the import, possession, use, and/or re-export to another country,
of encryption software. BEFORE using any encryption software,
please check your country's laws, regulations and policies
concerning the import, possession, or use, and re-export of
encryption software, to see if this is permitted.
See <http://www.wassenaar.org/> for more information.
The U.S. Government Department of Commerce, Bureau of Industry and Security (BIS),
has classified this software as Export Commodity Control Number (ECCN) 5D002.C.1,
which includes information security software using or performing
cryptographic functions with asymmetric algorithms.
The form and manner of this Apache Software Foundation distribution makes
it eligible for export under the License Exception
ENC Technology Software Unrestricted (TSU) exception
(see the BIS Export Administration Regulations, Section 740.13)
for both object code and source code.
The following provides more details on the included cryptographic software:
* Commons Crypto use [Java Cryptography Extension](http://docs.oracle.com/javase/8/docs/technotes/guides/security/crypto/CryptoSpec.html) provided by Java
* Commons Crypto link to and use [OpenSSL](https://www.openssl.org/) ciphers
74 downloads
Artifact commons-crypto
Group org.apache.commons
Version 1.2.0
Last update 14. January 2023
Organization not specified
URL https://commons.apache.org/proper/commons-crypto/
License Apache License, Version 2.0
Dependencies amount 1
Dependencies jna,
There are maybe transitive dependencies!
Group org.apache.commons
Version 1.2.0
Last update 14. January 2023
Organization not specified
URL https://commons.apache.org/proper/commons-crypto/
License Apache License, Version 2.0
Dependencies amount 1
Dependencies jna,
There are maybe transitive dependencies!
mahout from group org.apache.mahout (version 14.1)
Mahout's goal is to build scalable machine learning libraries. With scalable we mean: Scalable to
reasonably large data sets. Our core algorithms for clustering, classification and batch based collaborative
filtering are implemented on top of Apache Hadoop using the map/reduce paradigm. However we do not restrict
contributions to Hadoop based implementations: Contributions that run on a single node or on a non-Hadoop
cluster are welcome as well. The core libraries are highly optimized to allow for good performance also for
non-distributed algorithms. Scalable to support your business case. Mahout is distributed under a commercially
friendly Apache Software license. Scalable community. The goal of Mahout is to build a vibrant, responsive,
diverse community to facilitate discussions not only on the project itself but also on potential use cases. Come
to the mailing lists to find out more. Currently Mahout supports mainly four use cases: Recommendation mining
takes users' behavior and from that tries to find items users might like. Clustering takes e.g. text documents
and groups them into groups of topically related documents. Classification learns from existing categorized
documents what documents of a specific category look like and is able to assign unlabelled documents to the
(hopefully) correct category. Frequent itemset mining takes a set of item groups (terms in a query session,
shopping cart content) and identifies, which individual items usually appear together.
Group: org.apache.mahout Artifact: mahout
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Artifact mahout
Group org.apache.mahout
Version 14.1
Last update 16. July 2020
Organization The Apache Software Foundation
URL http://mahout.apache.org
License Apache License, Version 2.0
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
Group org.apache.mahout
Version 14.1
Last update 16. July 2020
Organization The Apache Software Foundation
URL http://mahout.apache.org
License Apache License, Version 2.0
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
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