WikipediaMiner is a toolkit for tapping the rich semantics encoded within Wikipedia. It makes it easy to integrate Wikipedia's knowledge into your own applications, by: providing simplified, object-oriented access to Wikipedia's structure and content.
measuring how terms and concepts in Wikipedia are connected to each other. detecting and disambiguating Wikipedia topics when they are mentioned in documents.
Wikipedia users constantly revise Wikipedia articles with updates happening almost each second. Hence, data stored in the official DBpedia endpoint can quickly become outdated, and Wikipedia articles need to be re-extracted. DBpedia-Live enables such a continuous synchronization between DBpedia and Wikipedia.
Faceted Wikipedia Search allows users to ask complex queries against Wikipedia. The answers to these queries are not generated using key word matching as the answers of search engines like Google or Yahoo, but are generated based on structured information that has been extracted from many different Wikipedia articles.
"Querying Wikipedia like a Semantic Database
DBpedia is a community effort to extract structured information from Wikipedia and make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia and to link other datasets on the Web to Wikipedia data."
The Semantic Wikipedia would combine the properties of the Semantic Web and Wiki technology. In this enhancement, articles would have properties (or traits), which could be mixed or combined to allow articles to be members of dynamic categories, chosen by user requests. Lists would no longer be just the numerous pre-formatted list articles, but rather, a list could be dynamically created for all articles matching selected search properties.
DBpedia.org is a project aiming to extract structured information from the information creadted as part of the Wikipedia project. This structured information is then made available on the World Wide Web.
"Wikidata is a collaboratively edited knowledge base hosted by the Wikimedia Foundation. It is a common source of open data that Wikimedia projects such as Wikipedia can use,[4][5] and anyone else, under a public domain license. The used data model is the Resource Description Framework. Wikidata is powered by the software Wikibase.[6]"
A Periodic Update of Semantic Web-related Research using Wikipedia One of the more popular posts of this AI3 blog was a listing of 99 research articles that used Wikipedia in one way or another to do semantic-Web related research.
UBY is a large-scale lexical-semantic resource for natural language processing (NLP) based on the ISO standard Lexical Markup Framework (LMF). UBY combines a wide range of information from expert-constructed and collaboratively constructed resources for English and German. Currently, UBY holds structurally and semantically interoperable versions of nine resources in two languages:
English WordNet, Wiktionary, Wikipedia, FrameNet and VerbNet,
German Wikipedia, Wiktionary and GermaNet, and multilingual OmegaWiki.
Category:Semantic Web Companies
From Wikipedia, the free encyclopedia
Companies that embrace semantic web technologies in their products.
Pages in category "Semantic Web Companies"
DBpedia is a project aiming to extract structured information from the information created as part of the Wikipedia project. This structured information is then made available on the World Wide Web. DBpedia allows users to query relationships and properties associated with Wikipedia resources, including links to other related datasets. DBpedia has been described by Tim Berners-Lee as one of the more famous parts of the Linked Data project.
YAGO2 is a huge semantic knowledge base, derived from Wikipedia, WordNet and GeoNames. Currently, YAGO2 has knowledge of more than 10 million entities (like persons, organizations, cities, etc.) and contains more than 120 million facts about these entities.
Tagpedia is a semantic reference useful to create sense-based descriptions of resources over the Web. In this way it wants to provide support to a better organization and access to semantically described Web contents in order to improve the management and the search for useful information.
The initial contents of Tagpedia has been extracted mining Wikipedia.
A semantic wiki is a wiki that has an underlying model of the knowledge described in its pages. Regular, or syntactic, wikis have structured text and untyped hyperlinks. Semantic wikis, on the other hand, provide the ability to capture or identify information about the data within pages, and the relationships between pages, in ways that can be queried or exported like a database.[1][2]
wiki contains the infobox-to-ontology and the table-to-ontology mappings which are used by the DBpedia extraction framework as well as the ontology definition itself. The framework collects the templates defined in this Wiki and extracts the Wikipedia content according to them (As of March 2010, only the dump extraction uses the mappings. DBpedia Live is going to follow shortly).
Multimedia Web Ontology Language (MOWL) has been designed to facilitate semantic interactions with multimedia contents. It supports perceptual modeling of concepts using expected media properties. While the reasoning in traditional ontology languages, e.g. Web Ontology Language (OWL), is based on Description Logics, MOWL supports a probabilistic reasoning framework based on Bayesian Network.