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- 8 creator masaki-aono.
- 8 creator md-hanif-seddiqui.
- 8 type InProceedings.
- 8 label "Alignment results of Anchor-Flood algorithm for OAEI-2008".
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- 8 abstract "Our proposed algorithm called Anchor-Flood algorithm, starts off withanchors. It gradually explores concepts by collecting neighbors in concept taxonomy,thereby taking advantage of locality of reference in the graph data structure.Then local alignment process runs over the collected small blocks of concepts.The process is repeated for the newly found aligned pairs. In this way, we cansignificantly reduce the computational time for the alignment as our algorithmconcentrates on the aligned pairs and it resolves the scalability problem in ontologyalignment over large ontologies. Through several experiments against OAEI-2008 datasets, we will demonstrate the results and the features of our Anchor-Flood algorithm.".
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- 8 title "Alignment results of Anchor-Flood algorithm for OAEI-2008".
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- 9 creator jerome-david.
- 9 type InProceedings.
- 9 label "AROMA results for OAEI 2008".
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- 9 abstract "This paper presents the results obtained by AROMA for its first participationto OAEI. AROMA is an hybrid, extensional and asymmetric ontologyalignment method which makes use of the association paradigm and a statisticalinterstingness measure, the implication intensity.".
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- 1 type InProceedings.
- 1 label "Reasoning over Dynamic Data in Expressive Knowledge Bases with Rscale".
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- 1 abstract "We introduce Rscale, a secondary storage-aware OWL 2 RL reasoning system capable of dealing with incremental additions and deletions of facts. Our initial evaluation indicates that Rscale is suitable for stream reasoning scenarios characterized by expressive reasoning tasks triggered by a moderate change frequency.".
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- 1 keyword "OWL 2 RL".
- 1 keyword "incremental updates".
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- 1 title "Reasoning over Dynamic Data in Expressive Knowledge Bases with Rscale".
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- 4 creator ralf-biedert.
- 4 creator thomas-roth-berghofer.
- 4 type InProceedings.
- 4 label "BetterRelations: Detailed Evaluation of a Game to Rate Linked Data Triples".
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- 4 abstract "While associations between concepts in our memory have different strengths, the explicit strengths Linked Data edge weights are missing. As a result Linked Data is of limited use for Artificial Intelligence with respect to the simulation of human thinking. In order to build a collection of such edge weights, we created a web-game prototype that ranks triples by importance. In this paper we explain the game's concept, summarize Linked Data related implementation aspects, and include a detailed evaluation of the game.".
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- 4 keyword "triple rating".
- 4 title "BetterRelations: Detailed Evaluation of a Game to Rate Linked Data Triples".
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