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Term Dependence on the Semantic Web

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Information about Term Dependence on the Semantic Web
Technology

Published on December 23, 2008

Author: gcheng

Source: slideshare.net

Description

Presentation given at ISWC2008. It analyzes complex network characteristics of dependence between terms (i.e. classes and properties) on the Semantic Web as well as dependence between Web ontologies.
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Term Dependence on the Semantic Web Gong Cheng and Yuzhong Qu Institute of Web Science (IWS) Southeast University, P.R. China at ISWC 2008, Karlsruhe, Germany

What is happening on the hypertext Web

How about the Semantic Web foaf:Person foaf:Agent wn:Agent-3 rdfs:subClassOf rdfs:subClassOf

Term Dependence Graph (TDG) foaf:Person foaf:Agent rdfs:subClassOf wn:Agent-3

Data Set As of April 2008 9.8 million well-formed RDF documents 114,408 hosts, or 7,290 registered domain names 400 million RDF triples http://iws.seu.edu.cn/services/falcons/

As of April 2008

9.8 million well-formed RDF documents

114,408 hosts, or 7,290 registered domain names

400 million RDF triples

Distribution of RDF documents on websites bio2rdf.org dbpedia.org openlinksw.com buzznet.com bibsonomy.org l3s.de …

Size distribution of RDF documents Maximum at 5 NCI Thesaurus WordNet

How large is the TDG analyzed 1,278,233 terms as nodes (from 3,039 vocabularies) 1,158,480 classes (90.6%) 118,808 properties (9.3%) 945 both (0.1%) 7,312,657 arcs (after removing self-loops)

1,278,233 terms as nodes (from 3,039 vocabularies)

1,158,480 classes (90.6%)

118,808 properties (9.3%)

945 both (0.1%)

7,312,657 arcs (after removing self-loops)

Distribution of terms in vocabularies EthanAnimals OpenCyc DBpedia properties EthanAnimals FMA

Degree analysis of TDG In-degree: direct influence degree Out-degree: direct dependence degree Average in-/out-degree: 5.72

In-degree: direct influence degree

Out-degree: direct dependence degree

Average in-/out-degree: 5.72

In-degree rdf:type rdfs:subClassOf owl:Class rdfs:label rdfs:comment rdfs:Class owl:equivalentClass … cyc:guid … 64.9%

Out-degree 40.9% at 5 Focal classes

Correlation Pearson’s correlation coefficient between in-degrees and out-degrees 0.006 ∈ [-1, 1]

Pearson’s correlation coefficient between in-degrees and out-degrees

0.006 ∈ [-1, 1]

Distance analysis of TDG foaf:Person foaf:Agent rdfs:subClassOf wn:Agent-3

Dependence depth Average dependence depth: 10 Leaf classes in FMA

Hop plot and effective diameter

Connectivity analysis of TDG 93.4% in FMA

Connectivity analysis of TDG over 40,000 disconnected pieces after 16 nodes are removed

Vocabulary Dependence Graph (VDG) foaf:Person foaf:Agent rdfs:subClassOf wn:Agent-3 foaf rdfs wn

How large is the VDG analyzed 3,039 vocabularies as nodes 11,392 arcs (after removing self-loops)

3,039 vocabularies as nodes

11,392 arcs (after removing self-loops)

Degree analysis of VDG rdf, rdfs, owl, daml Average in-/out-degree: 3.75

Distance analysis of VDG

Connectivity analysis of VDG

Main results Power-laws Complex structures within ontologies long distance between terms Only a few links between ontologies (excluding language-level ontologies) All the data are available online.

Power-laws

Complex structures within ontologies

long distance between terms

Only a few links between ontologies (excluding language-level ontologies)

All the data are available online.

More words Linking Open Data (LOD) Linking Ontologies on the Web (LOW) third-party links, e.g. ontology matching publishing links online (collaboratively)

Linking Open Data (LOD)

Linking Ontologies on the Web (LOW)

third-party links, e.g. ontology matching

publishing links online (collaboratively)

Thank you for your attention yu`yiwon 语义网 Semantic Web shu`shin 属性 Property ley 类 Class benty 本体 Ontology P ronunciation Chinese English

Power-law

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