Characterizing the semantic web on the web

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Reference:

  1. Li Ding, Tim Finin. Characterizing the Semantic Web on the Web , Proceedings of the Fifth International Semantic Web Conference (ISWC06), 2006

bibtex


@inproceedings { KSL-06-15 ,
author = "Li Ding, Tim Finin",
booktitle = "Proceedings of the Fifth International Semantic Web Conference (ISWC06)",
title = "Characterizing the Semantic Web on the Web",
year = "2006",
}

abstract: Semantic Web languages are being used to represent, encode and exchange semantic data in many contexts beyond the Web - in databases, multi-agent systems, mobile computing, and ad hoc networking environments. The core paradigm, however, remains what we call the Web aspect of the Semantic Web - its use by independent and distributed agents who publish and consume data on the World Wide Web. To better understand this central use case, we have harvested and analyzed a collection of Semantic Web documents from an estimated ten million available on the Web. Using a corpus of more than 1.7 million documents comprising over 300 million RDF triples, we describe a number of global metrics, properties and usage patterns. Most of the metrics, such as the size of Semantic Web documents and the use frequency of Semantic Web terms, were found to follow a power law distribution.

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Facts about Characterizing the semantic web on the webRDF feed
AbstractSemantic Web languages are being used to r Semantic Web languages are being used to represent, encode and exchange semantic data in many contexts beyond the Web - in databases, multi-agent systems, mobile computing, and ad hoc networking environments. The core paradigm, however, remains what we call the Web aspect of the Semantic Web - its use by independent and distributed agents who publish and consume data on the World Wide Web. To better understand this central use case, we have harvested and analyzed a collection of Semantic Web documents from an estimated ten million available on the Web. Using a corpus of more than 1.7 million documents comprising over 300 million RDF triples, we describe a number of global metrics, properties and usage patterns. Most of the metrics, such as the size of Semantic Web documents and the use frequency of Semantic Web terms, were found to follow a power law distribution. found to follow a power law distribution.
AddressAthens, GA  +
AuthorLi Ding  +, and Tim Finin  +
Bibtypeinproceedings  +
BooktitleProceedings of the Fifth International Semantic Web Conference (ISWC06)  +
KeyKSL-06-15  +
MonthNovember  +
RelationSwoogle  +, and Inference web  +
TagComputer science  +
TitleCharacterizing the Semantic Web on the Web  +
Tr idKSL-06-15  +
Year2006  +
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