Matches in ScholarlyData for { ?s ?p ?o. }
- 138 type InProceedings.
- 138 label "Understanding Justifications for Entailments in OWL".
- 138 sameAs 138.
- 138 abstract "Recent work in explanation of entailments in ontologies has focused on justifications and their variants. While in many cases, just presenting the justification is sufficient for user understanding, and in all cases justifications are much better than nothing, we have empirically identified cases where understanding how a justification supports an entailment is inordinately difficult. Indeed there are naturally occurring justifications that people, with varying expertise in OWL, cannot understand. To address this problem, we have developed a novel conceptual framework for justification oriented proofs. Given a justification for an entailment in an ontology, intermediate inference steps, called lemmas, are automatically derived, that bridge the gap between the axioms in the justification and the entailment. The proof shows in a stepwise way how the lemmas and ultimately the entailment follow from the justification. At the heart of the framework is the notion of a ``complexity model'', which predicts how easy or difficult it is for a user to understand a justification, and is used for selecting the lemmas to insert into a proof. This poster and demo presents this framework backed by a prototype implementation.".
- 138 hasAuthorList authorList.
- 138 hasTopic Semantic_Web.
- 138 isPartOf proceedings.
- 138 title "Understanding Justifications for Entailments in OWL".
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- item-1 hasContent matthew-horridge.
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- item-2 hasContent bijan-parsia.
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- item-3 type ListItem.
- item-3 hasContent ulrike-sattler.
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- 139 creator daniele-dellaglio.
- 139 creator emanuele-della-valle.
- 139 creator irene-celino.
- 139 type InProceedings.
- 139 label "The alpha Urban LarKC, a Semantic Urban Computing application".
- 139 sameAs 139.
- 139 abstract "This paper describes the alpha Urban LarKC, one of the first Urban Computing applications built with Semantic Web technologies. It is based on the LarKC platform and makes use of the publicly available data sources on the Web which refer to interesting information about a urban environment (the city of Milano in Italy).".
- 139 hasAuthorList authorList.
- 139 hasTopic Semantic_Web.
- 139 isPartOf proceedings.
- 139 title "The alpha Urban LarKC, a Semantic Urban Computing application".
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- item-1 hasContent emanuele-della-valle.
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- item-2 hasContent irene-celino.
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- item-3 hasContent daniele-dellaglio.
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- 140 creator na-hong.
- 140 creator ying-ding.
- 140 creator zhixiong-zhang.
- 140 type InProceedings.
- 140 label "Semantic-Powered Research Profiling".
- 140 sameAs 140.
- 140 abstract "Research profiling is a widely-adopted method to monitor research development and rank research performance. This paper describes a novel infrastructure to generate semantic-powered research profiling for research fields, organizations and individuals. It crawls related websites and news feeds, extracts research terms, research objects and relations from them and uses the proposed Research Ontology to model them into RDF triples to facilitate semantic queries and semantic mining on burst detection, hot topic detection, dynamics of research, and relation mining. The authors implement a research profiling experiment in Artificial Intelligence area to show the effectiveness of the research profiling based on semantic mining.".
- 140 hasAuthorList authorList.
- 140 hasTopic Semantic_Web.
- 140 isPartOf proceedings.
- 140 title "Semantic-Powered Research Profiling".
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- item-1 hasContent zhixiong-zhang.
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- item-2 hasContent ying-ding.
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- item-3 hasContent na-hong.
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- 143 creator andreas-abecker.
- 143 creator mark-hefke.
- 143 type InProceedings.
- 143 label "Leadsto - Collaboratively Constructing and Discovering Causal Chains".
- 143 sameAs 143.
- 143 abstract "Leadsto is a prototypical Semantic Portal for collaboratively describing statements of the form x leads to y (e.g. accident leads to traffic jam). Existing elements of statements (precedents, antecedents) can be linked with each other, and completely new elements can be created. Individual statements can be created and the set of stored statements further extended and developed collaboratively on the Web by humans; in addition, automated approaches for extracting further statements from any web page are employed. The constantly growing net-like structure can be searched and navigated. The major benefit of the system is to automatically discover and make available causal chains of the form x leads to y , y leads to z , etc. (as well as the reverse direction). In this way, not yet known facts as well as their provenance can be collaboratively discovered by the wisdom of a crowd.".
- 143 hasAuthorList authorList.
- 143 hasTopic Semantic_Web.
- 143 isPartOf proceedings.
- 143 title "Leadsto - Collaboratively Constructing and Discovering Causal Chains".
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- item-1 type ListItem.
- item-1 hasContent mark-hefke.
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- item-2 hasContent andreas-abecker.
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- 144 creator bernhard-schandl.