Download JAR files tagged by scalable with all dependencies
luzzu-annotations from group io.github.luzzu (version 4.0.0)
Artifact luzzu-annotations
Group io.github.luzzu
Version 4.0.0
Last update 26. October 2018
Organization not specified
URL Not specified
License not specified
Dependencies amount 3
Dependencies luzzu-semantics, luzzu-assessment, luzzu-lowlevel-operations,
There are maybe transitive dependencies!
Group io.github.luzzu
Version 4.0.0
Last update 26. October 2018
Organization not specified
URL Not specified
License not specified
Dependencies amount 3
Dependencies luzzu-semantics, luzzu-assessment, luzzu-lowlevel-operations,
There are maybe transitive dependencies!
luzzu-assessment from group io.github.luzzu (version 4.0.0)
Artifact luzzu-assessment
Group io.github.luzzu
Version 4.0.0
Last update 26. October 2018
Organization not specified
URL Not specified
License not specified
Dependencies amount 3
Dependencies luzzu-semantics, luzzu-lowlevel-operations, luzzu-ld-qualitymetrics-commons,
There are maybe transitive dependencies!
Group io.github.luzzu
Version 4.0.0
Last update 26. October 2018
Organization not specified
URL Not specified
License not specified
Dependencies amount 3
Dependencies luzzu-semantics, luzzu-lowlevel-operations, luzzu-ld-qualitymetrics-commons,
There are maybe transitive dependencies!
luzzu from group io.github.luzzu (version 4.0.0)
Luzzu is a Quality Assessment Framework for Linked Open Datasets. It is
a generic framework based on the Dataset Quality Ontology (daQ),
allowing users to define their own quality metrics. Luzzu is an
integrated platform that:
- assesses Linked Data quality using a library of generic and
user-provided domain specific quality metrics in a scalable manner;
- provides queryable quality metadata on the assessed datasets;
- assembles detailed quality reports on assessed datasets.
Furthermore, the infrastructure:
- scales for the assessment of big datasets;
- can be easily extended by the users by creating their custom and
domain-specific pluggable metrics, either by employing a novel
declarative quality metric specification language or conventional
imperative plugins;
- employs a comprehensive ontology framework for representing and
exchanging all quality related information in the assessment workflow;
- implements quality-driven dataset ranking algorithms facilitating
use-case driven discovery and retrieval.
Group: io.github.luzzu Artifact: luzzu
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Artifact luzzu
Group io.github.luzzu
Version 4.0.0
Last update 26. October 2018
Organization ADAPT Centre, Trinity College Dublin, Ireland
URL https://luzzu.github.io/Framework/
License GNU GENERAL PUBLIC LICENSE, Version 2.0
Dependencies amount 15
Dependencies hamcrest-all, apache-jena-libs, jena-core, log4j, slf4j-api, jcl-over-slf4j, slf4j-log4j12, slf4j-jdk14, commons-collections4, jackson-core, httpclient, httpcore, httpcore-nio, httpasyncclient, httpasyncclient-cache,
There are maybe transitive dependencies!
Group io.github.luzzu
Version 4.0.0
Last update 26. October 2018
Organization ADAPT Centre, Trinity College Dublin, Ireland
URL https://luzzu.github.io/Framework/
License GNU GENERAL PUBLIC LICENSE, Version 2.0
Dependencies amount 15
Dependencies hamcrest-all, apache-jena-libs, jena-core, log4j, slf4j-api, jcl-over-slf4j, slf4j-log4j12, slf4j-jdk14, commons-collections4, jackson-core, httpclient, httpcore, httpcore-nio, httpasyncclient, httpasyncclient-cache,
There are maybe transitive dependencies!
luzzu-webapp from group de.unibonn.iai.eis (version 2.0.1)
0 downloads
Artifact luzzu-webapp
Group de.unibonn.iai.eis
Version 2.0.1
Last update 09. June 2017
Organization not specified
URL Not specified
License not specified
Dependencies amount 6
Dependencies luzzu-semantics, commons-codec, luzzu-operations, guava, jackson-mapper-asl, jackson-core-asl,
There are maybe transitive dependencies!
Group de.unibonn.iai.eis
Version 2.0.1
Last update 09. June 2017
Organization not specified
URL Not specified
License not specified
Dependencies amount 6
Dependencies luzzu-semantics, commons-codec, luzzu-operations, guava, jackson-mapper-asl, jackson-core-asl,
There are maybe transitive dependencies!
luzzu-annotations from group de.unibonn.iai.eis (version 2.0.1)
Group: de.unibonn.iai.eis Artifact: luzzu-annotations
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Artifact luzzu-annotations
Group de.unibonn.iai.eis
Version 2.0.1
Last update 09. June 2017
Organization not specified
URL Not specified
License not specified
Dependencies amount 3
Dependencies luzzu-semantics, luzzu-assessment, luzzu-operations,
There are maybe transitive dependencies!
Group de.unibonn.iai.eis
Version 2.0.1
Last update 09. June 2017
Organization not specified
URL Not specified
License not specified
Dependencies amount 3
Dependencies luzzu-semantics, luzzu-assessment, luzzu-operations,
There are maybe transitive dependencies!
luzzu-assessment from group de.unibonn.iai.eis (version 2.0.1)
Group: de.unibonn.iai.eis Artifact: luzzu-assessment
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Show all versions Show documentation Show source
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Artifact luzzu-assessment
Group de.unibonn.iai.eis
Version 2.0.1
Last update 09. June 2017
Organization not specified
URL Not specified
License not specified
Dependencies amount 1
Dependencies luzzu-semantics,
There are maybe transitive dependencies!
Group de.unibonn.iai.eis
Version 2.0.1
Last update 09. June 2017
Organization not specified
URL Not specified
License not specified
Dependencies amount 1
Dependencies luzzu-semantics,
There are maybe transitive dependencies!
luzzu from group de.unibonn.iai.eis (version 2.0.1)
Luzzu is a Quality Assessment Framework for Linked Open Datasets. It is
a generic framework based on the Dataset Quality Ontology (daQ),
allowing users to define their own quality metrics. Luzzu is an
integrated platform that:
- assesses Linked Data quality using a library of generic and
user-provided domain specific quality metrics in a scalable manner;
- provides queryable quality metadata on the assessed datasets;
- assembles detailed quality reports on assessed datasets.
Furthermore, the infrastructure:
- scales for the assessment of big datasets;
- can be easily extended by the users by creating their custom and
domain-specific pluggable metrics, either by employing a novel
declarative quality metric specification language or conventional
imperative plugins;
- employs a comprehensive ontology framework for representing and
exchanging all quality related information in the assessment workflow;
- implements quality-driven dataset ranking algorithms facilitating
use-case driven discovery and retrieval.
Group: de.unibonn.iai.eis Artifact: luzzu
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Artifact luzzu
Group de.unibonn.iai.eis
Version 2.0.1
Last update 09. June 2017
Organization Enterprise Information Systems - University of Bonn
URL http://eis-bonn.github.io/Luzzu/
License GNU GENERAL PUBLIC LICENSE, Version 2.0
Dependencies amount 10
Dependencies mockito-core, hamcrest-all, apache-jena-libs, log4j, slf4j-api, jcl-over-slf4j, slf4j-log4j12, slf4j-jdk14, commons-collections4, jackson-core-asl,
There are maybe transitive dependencies!
Group de.unibonn.iai.eis
Version 2.0.1
Last update 09. June 2017
Organization Enterprise Information Systems - University of Bonn
URL http://eis-bonn.github.io/Luzzu/
License GNU GENERAL PUBLIC LICENSE, Version 2.0
Dependencies amount 10
Dependencies mockito-core, hamcrest-all, apache-jena-libs, log4j, slf4j-api, jcl-over-slf4j, slf4j-log4j12, slf4j-jdk14, commons-collections4, jackson-core-asl,
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!
mahout-eclipse-support from group org.apache.mahout (version 0.5)
Artifact mahout-eclipse-support
Group org.apache.mahout
Version 0.5
Last update 28. May 2011
Organization not specified
URL Not specified
License not specified
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
Group org.apache.mahout
Version 0.5
Last update 28. May 2011
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
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!
Group org.apache.mahout
Version 0.3
Last update 12. March 2010
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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