DBpedia Spotlight is a tool for annotating mentions of DBpedia resources in text, providing a solution for linking unstructured information sources to the Linked Open Data cloud through DBpedia. DBpedia Spotlight performs named entity extraction, including entity detection and Name Resolution (a.k.a. disambiguation). It can also be used for building your solution for Named Entity Recognition, amongst other information extraction tasks.
Elefant (Efficient Learning, Large-scale Inference, and Optimisation Toolkit) is an open source library for machine learning licensed under the Mozilla Public License (MPL). We develop an open source machine learning toolkit which provides
algorithms for machine learning utilising the power of multi-core/multi-threaded processors/operating systems (Linux, WIndows, Mac OS X),
a graphical user interface for users who want to quickly prototype machine learning experiments,
tutorials to support learning about Statistical Machine Learning (Statistical Machine Learning at The Australian National University), and
detailed and precise documentation for each of the above.
Clerezza is a service platform based on OSGi (Open Services Gateway initiative) which provides a set of functionality for management of semantically linked data accessible through RESTful Web Services and in a secured way. Furthermore, Clerezza allows to easily develop semantic web applications by providing tools to manipulate RDF data, create RESTful Web Services and Renderlets using ScalaServerPages.
The Visualization ToolKit (VTK) is an open source, freely available software system for 3D computer graphics, image processing, and visualization used by thousands of researchers and developers around the world.
Developed by the Lawrence Livermore National Laboratory, VisIt contains a rich set of visualization methods—such as contour plots, pseudocolor plots, volume plots, vector plots, and boundary plots—for visualizing scientific data. VisIt allows the ability to provide quantitative as well as qualitative information from a scientific data set.
The Fresnel Vocabulary for RDF provides a way to write down a set of instructions for transforming RDF statements into HTML for display. For some time, the ORDF library has included two implementations of Fresnel, one in JavaScript and one in Python. Recently added is a command line tool, simply called fresnel, for rendering HTML documents given a lens and an RDF graph.
Tupelo is a data and metadata management system based on semantic web technologies. Tupelo provides a variety of generic utilities for managing data and metadata using both best-of-breed semantic database implementations such as Jena and Sesame, as well as ordinary storage technologies such as flat files. Tupelo makes data and metadata portable across a variety of Contexts and deployment scenarios, including desktop applications, web-based applications, and more complex distributed architectures. Its use of global identification and explicit semantics means that metadata created and managed with Tupelo can be easily exported and used by a wide variety of RDF-aware tools and technologies.
Markov Logic Networks (MLNs) is a powerful framework that combines statistical and logical reasoning; they have been applied to many data intensive problems including information extraction, entity resolution, text mining, and natural language processing. Based on principled data management techniques, Tuffy is an MLN inference engine that achieves scalability and orders of magnitude speedup compared to prior art implementations. It is written in Java and relies on PostgreSQL. For a brief introduction to MLNs and the technical details of Tuffy, please see our technical report.
The Car Options Ontology is designed to be used in combination with GoodRelations for the commercial aspects of offers for sale or rental, and the Vehicle Sales Ontology for car features.
A workshop of the 10th International Semantic Web Conference (ISWC 2011), 23-27 October 2011, Bonn, Germany.
The goal of the Semantic Sensor Networks workshop is to develop an understanding of the ways semantic web technologies, including ontologies, agent architectures and semantic web services, can contribute to the growth, application and deployment of large-scale sensor networks and their applications. The workshop provides an inter-disciplinary forum to explore and promote these concepts.
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