Matches in ScholarlyData for { ?s ?p ?o. }
- 71 keyword "data framework".
- 71 keyword "ontologies - modular".
- 71 keyword "semantic data integration".
- 71 keyword "semantic data registration".
- 71 keyword "semantic networks".
- 71 title "Semantic Data Integration and Registration: Application to heterogeneous atmosphere and volcanic data sources".
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- item-1 hasContent deborah-mcguinness.
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- 72 creator bhavani-thuraisingham.
- 72 creator jeff-partyka.
- 72 creator latifur-khan.
- 72 creator neda-alipanah.
- 72 creator shashi-shekhar.
- 72 type InProceedings.
- 72 label "Ontology Alignment Using Multiple Contexts".
- 72 sameAs 72.
- 72 abstract "Ontology alignment involves determining the semantic heterogeneity between two or more domain specifications by considering their associated concepts. Our approach considers name, structural and content matching techniques for aligning ontologies. After comparing the ontologies using concept names, we examine the instance data of the compared concepts and perform content matching using value types based on N-grams and Entropy Based Distribution (EBD). Although these approaches are generally sufficient, additional methods may be required. Subsequently, we compare the structural characteristics between concepts using Expectation-Maximization (EM). To illustrate our approach, we conducted experiments using authentic geographic information systems (GIS) data and generate results which clearly demonstrate the utility of the algorithms while emphasizing the contribution of structural matching.".
- 72 hasAuthorList authorList.
- 72 isPartOf poster_demo_proceedings.
- 72 keyword "Geographic Information Systems".
- 72 keyword "Ontology".
- 72 title "Ontology Alignment Using Multiple Contexts".
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- 73 creator akimichi-tanaka.
- 73 creator makoto-nakatsuji.
- 73 creator toru-ishida.
- 73 type InProceedings.
- 73 label "Extracting Communities of Interests for Semantics-based Graph Searches".
- 73 sameAs 73.
- 73 abstract "We propose an algorithm that mines blog entries to realize Semantic Web searches. It divides a graph, whose vertices are users and whose edges represent shared interests, into subgraphs - communities of interests (COIs). The algorithm allows users to identify new interests quickly and accurately. Our algorithm differs from conventional modularity-based approaches because it attaches semantic tags to the relationships between COIs or between users based on taxonomies of the content items of interest. We also introduce a mechanism to harmonize the number of users in each COI. Our two proposals raise the effectiveness of information searches.".
- 73 hasAuthorList authorList.
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- 73 keyword "community extraction".
- 73 keyword "community of interests".
- 73 keyword "semantic-based graph search".
- 73 title "Extracting Communities of Interests for Semantics-based Graph Searches".
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- item-1 hasContent makoto-nakatsuji.
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