Matches in ScholarlyData for { ?s ?p ?o. }
- 125 type InProceedings.
- 125 label "Optimizing Enterprise-scale OWL 2 RL Reasoning in a Relational Database System".
- 125 sameAs 125.
- 125 abstract "OWL 2 RL was standardized as a less expressive but scalable subset of OWL 2 that allows a forward-chaining implementation. However, building an enterprise-scale forward-chaining based inference engine that can 1) take advantage of modern multi-core computer architectures, and 2) efficiently update inference for additions remains a challenge. In this paper, we present an OWL 2 RL inference engine implemented inside the Oracle database system, using novel techniques for parallel processing that can readily scale on multi-core machines and clusters. Additionally, we have added support for efficient incremental maintenance of the inferred graph after triple additions. Finally, to handle the increasing number of owl:sameAs relationships present in Semantic Web datasets, we have provided a hybrid in-memory/disk based approach to efficiently compute compact equivalence closures. We have done extensive testing to evaluate these new techniques; the test results demonstrate that our inference engine is capable of performing efficient inference over ontologies with billions of triples using a modest hardware configuration.".
- 125 hasAuthorList authorList.
- 125 isPartOf proceedings.
- 125 keyword "semantic web".
- 125 title "Optimizing Enterprise-scale OWL 2 RL Reasoning in a Relational Database System".
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- item-1 hasContent vladimir-kolovski.
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- item-2 hasContent zhe-wu.
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- item-3 hasContent george-eadon.
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- 126 creator achille-fokoue.
- 126 creator mudhakar-srivatsa.
- 126 creator rob-young.
- 126 type InProceedings.
- 126 label "Assessing Trust in Uncertain Information".
- 126 sameAs 126.
- 126 abstract "On the Semantic Web, decision makers (humans or software agents alike) are faced with the challenge of examining large volumes of information originating from heterogeneous sources with the goal of ascertaining trust in various pieces of information. While previous work has focused on simple models for review and rating systems, we introduce a new trust model for rich, complex and uncertain information.We present the challenges raised by the new model, and the results of an evaluation of the first prototype implementation under a variety of scenarios.".
- 126 hasAuthorList authorList.
- 126 isPartOf proceedings.
- 126 keyword "semantic web".
- 126 title "Assessing Trust in Uncertain Information".
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- item-1 hasContent achille-fokoue.
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- item-2 hasContent mudhakar-srivatsa.
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- item-3 hasContent rob-young.
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- 127 creator heather-s-packer.
- 127 creator nicholas-gibbins.
- 127 creator nicholas-r-jennings.
- 127 type InProceedings.
- 127 label "Forgetting Fragments from Evolving Ontologies".
- 127 sameAs 127.
- 127 abstract "Ontologies underpin the semantic web; they define the concepts and their relationships contained in a data source. An increasing number of ontologies are available on-line, but an ontology that combines information from many different sources can grow extremely large. As an ontology grows larger, more resources are required to use it, and its response time becomes slower. Thus, we present and evaluate an on-line approach that forgets fragments from an OWL ontology that are infrequently or no longer used, or are cheap to relearn, in terms of time and resources. In order to evaluate our approach, we situate it in a controlled simulation environment, RoboCup OWLRescue, which is an extension of the widely used RoboCup Rescue platform, which enables agents to build ontologies automatically based on the tasks they are required to perform. We benchmark our approach against other comparable techniques and show that agents using our approach spend less time forgetting concepts from their ontology, allowing them to spend more time deliberating their actions, to achieve a higher average score in the simulation environment.".
- 127 hasAuthorList authorList.
- 127 isPartOf proceedings.
- 127 keyword "classification".
- 127 keyword "linked open data".
- 127 keyword "named entity".
- 127 keyword "semantic web".
- 127 title "Forgetting Fragments from Evolving Ontologies".
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- item-1 hasContent heather-s-packer.
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- item-2 hasContent nicholas-gibbins.
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- item-3 hasContent nicholas-r-jennings.
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- 131 creator paul-groth.
- 131 creator shenghui-wang.
- 131 type InProceedings.
- 131 label "Measuring the dynamic bi-directional influence between content and social networks".
- 131 sameAs 131.
- 131 abstract "The Social Semantic Web has begun to provide connections between users within social networks and the content they produce across the whole of the Social Web. Thus, the Social Semantic Web provides a basis to analyze both the communication behavior of users together with the content of their communication. However, there is little research combining the tools to study communication behaviour and communication content, namely, social network analysis and content analysis. Furthermore, there is even less work addressing the longitudinal characteristics of such a combination. This paper presents a general framework for measuring the dynamic bi-directional influence between communication content and social networks. We apply this framework in two use-cases: online forum discussions and conference publications. The results provide a new perspective over the dynamics involving both social networks and communication content.".
- 131 hasAuthorList authorList.
- 131 isPartOf proceedings.
- 131 keyword "semantic web".
- 131 title "Measuring the dynamic bi-directional influence between content and social networks".
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- item-1 hasContent shenghui-wang.
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