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wicketstuff-servlet3 from group org.wicketstuff (version 6.30.0)

Group: org.wicketstuff Artifact: wicketstuff-servlet3
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Artifact wicketstuff-servlet3
Group org.wicketstuff
Version 6.30.0
Last update 15. December 2018
Newest version Yes
Organization not specified
URL http://maven.apache.org
License not specified
Dependencies amount 2
Dependencies servlet-api, junit,
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circuit4stream_2.12 from group com.github.norwae (version 1.0.0)

This module packages a circuit breaker that can be used to avoid overloading or otherwise depending on a temporarily unavailable (remote) system. The central use of the circuit breaker is to prevent failures from one system to cascade to other systems in an unchecked manner. Thus, our implementation is chiefly concerned with replacing a failing component with another component that fails in a very predictable manner. These failures are not "dropped" or otherwise made invisible, and still need to be handled, but they will occur in a predictable, and hopefully usable manner.

Group: com.github.norwae Artifact: circuit4stream_2.12
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Artifact circuit4stream_2.12
Group com.github.norwae
Version 1.0.0
Last update 10. May 2019
Newest version Yes
Organization com.github.norwae
URL https://github.com/norwae/circuit4stream
License MIT
Dependencies amount 2
Dependencies scala-library, akka-stream_2.12,
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HermiT from group com.github.ansell.hermit (version 1.3.8.2-ansell)

HermiT is reasoner for ontologies written using the Web Ontology Language (OWL). Given an OWL file, HermiT can determine whether or not the ontology is consistent, identify subsumption relationships between classes, and much more. This is the maven build of HermiT and is designed for people who wish to use HermiT from within the OWL API. It is not officially supported by the HermiT development team, but was built initially for use with the Clojure-OWL library. It is built using the HermiT source tree without modification. There have been some additions to the test source tree to account for differences between the maven and ant environment; these are small and (hopefully) maintainable. The version number of this package is a composite of the HermiT version and an value representing releases of this packaged version. So, 1.3.7.1 is the first release of the mavenized version of HermiT based on the 1.3.7 release of HermiT. This package includes the Jautomata library (http://jautomata.sourceforge.net/), and builds with it directly. This library appears to be no longer under active development, and so a "fork" seems appropriate. No development is intended or anticipated on this code base.

Group: com.github.ansell.hermit Artifact: HermiT
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2 downloads
Artifact HermiT
Group com.github.ansell.hermit
Version 1.3.8.2-ansell
Last update 03. September 2013
Newest version Yes
Organization not specified
URL http://hermit-reasoner.com/
License LGPL
Dependencies amount 12
Dependencies owlapi-api, owlapi-impl, owlapi-parsers, owlapi-rio, sesame-rio-turtle, sesame-rio-ntriples, sesame-rio-rdfxml, axiom-api, axiom-c14n, axiom-impl, axiom-dom, automaton,
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mahout from group org.apache.mahout (version 0.13.0)

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 0.13.0
Last update 15. April 2017
Newest version Yes
Organization The Apache Software Foundation
URL http://mahout.apache.org
License Apache License, Version 2.0
Dependencies amount 0
Dependencies No dependencies
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mahout-eclipse-support from group org.apache.mahout (version 0.5)

Group: org.apache.mahout Artifact: mahout-eclipse-support
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1 downloads
Artifact mahout-eclipse-support
Group org.apache.mahout
Version 0.5
Last update 28. May 2011
Newest version Yes
Organization not specified
URL Not specified
License not specified
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!

mahout-parent from group org.apache.mahout (version 0.3)

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, classfication 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 exisiting 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-parent
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Artifact mahout-parent
Group org.apache.mahout
Version 0.3
Last update 12. March 2010
Newest version Yes
Organization The Apache Software Foundation
URL http://lucene.apache.org/mahout
License The Apache Software License, Version 2.0
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!



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