Matches in ScholarlyData for { ?s ?p ?o. }
- 8 hasAuthorList authorList.
- 8 isPartOf proceedings.
- 8 keyword "context".
- 8 keyword "ontology".
- 8 keyword "semantic".
- 8 keyword "spatial".
- 8 title "Geospatial Semantic Context Capturing for Picture Annotation, Retrieval and Visualization in SPIM".
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- item-1 hasContent stavros-christodoulakis.
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- item-2 hasContent michalis-foukarakis.
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- item-3 hasContent lemonia-ragia.
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- item-4 hasContent hiroaki-uchiyama.
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- item-5 hasContent takuya-imai.
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- 1 creator alireza-sadeghian.
- 1 creator bart-gajderowicz.
- 1 type InProceedings.
- 1 label "Ontology Granulation Through Inductive Decision Trees".
- 1 sameAs 1.
- 1 abstract "The popularity of ontologies for representing the semantics behind many real-world domains has created a growing pool of ontologies on various topics. While different ontologists, experts, and organizations create the vast majority of ontologies, often for closed world systems, their domains frequently overlap in an open world system, such as the Semantic Web. These overlapping ontologies sometimes model similar or matching theories, that may be inconsistent. To assist in the reuse of these ontologies, this paper describes a technique for enriching manually created ontologies by supplementing them with inductively derived rules, and reducing the number of inconsistencies. The derived rules are translated from decision trees created by executing a tree based data mining algorithm with probability measures over the data being modeled. These rules can be used to revise the ontology adding a higher level of granularity, in order to identify possible similarities missed by the original ontologists. We then discuss how this may be applied to ontology matching. We demonstrate the application of our technique by presenting an example, and discuss how various data types may be treated to generalize the semantics of an ontology for an open world system.".
- 1 hasAuthorList authorList.
- 1 isPartOf proceedings.
- 1 keyword "decision trees".
- 1 keyword "ontology granulation".
- 1 keyword "ontology matching".
- 1 keyword "probabilistic ontology".
- 1 title "Ontology Granulation Through Inductive Decision Trees".
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- item-1 hasContent bart-gajderowicz.
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- item-2 hasContent alireza-sadeghian.
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- 2 creator claudia-damato.
- 2 creator floriana-esposito.
- 2 creator nicola-fanizzi.
- 2 type InProceedings.
- 2 label "Evidential Nearest-Neighbors Classification for Inductive ABox Reasoning".
- 2 sameAs 2.
- 2 abstract "In the line of our investigation on inductive methods for Semantic Web reasoning, we propose an alternative way for approximate ABox reasoning based on the analogical principle of the nearest-neighbors. Once neighbors of a test individual are selected, a combination rule descending from the Dempster-Shafer theory can join together the evidence provided by the neighbor individuals. We show how to exploit the procedure for determining unknown class- and role-memberships or fillers for datatype properties which may be the basis for many further ABox inductive reasoning algorithms.".
- 2 hasAuthorList authorList.
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- 2 title "Evidential Nearest-Neighbors Classification for Inductive ABox Reasoning".
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- item-1 hasContent nicola-fanizzi.
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- item-2 hasContent claudia-damato.
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- item-3 hasContent floriana-esposito.
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- 3 creator bettina-fazzinga.
- 3 creator claudia-damato.
- 3 creator georg-gottlob.
- 3 creator nicola-fanizzi.
- 3 creator thomas-lukasiewicz.
- 3 type InProceedings.
- 3 label "Combining Semantic Web Search with the Power of Inductive Reasoning".
- 3 sameAs 3.
- 3 abstract "Extensive research activities are recently directed towards the Semantic Web as a future form of the Web. Consequently, Web search as the key technology of the Web is evolving towards some novel form of Semantic Web search. A very promising recent approach to such SemanticWeb search is based on combining standard Web search with ontological background knowledge and using standard Web search engines as the main inference motor of Semantic Web search. In this paper, we propose to further enhance this approach to Semantic Web search by the use of inductive reasoning techniques. This adds especially the important ability to handle inconsistencies, noise, and incompleteness, which are very likely to occur in distributed and heterogeneous environments, such as the Web. We report on a prototype implementation of the new approach and extensive experimental results.".
- 3 hasAuthorList authorList.
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- 3 title "Combining Semantic Web Search with the Power of Inductive Reasoning".
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