Matches in ScholarlyData for { ?s ?p ?o. }
- 52 label "Towards Evaluating Interactive Ontology Matching Tools".
- 52 sameAs 52.
- 52 abstract "With a growing number of ontologies used on the semantic web, agents can fully make sense of different datasets only if correspondences between those ontologies are known. Ontology matching tools have been proposed to find such correspondences. While the current research focus is mainly on fully automatic matching tools, some approaches have been proposed that involve the user in the matching process. However, there are currently no benchmarks and test methods to compare such tools. In this paper, we introduce a number of quality measures for interactive ontology matching tools, and we discuss means to automatically run benchmark tests for such tools. To demonstrate those evaluations, we show examples on assessing the quality of interactive matching tools which involve the user in matcher selection and matcher parametrization.".
- 52 hasAuthorList authorList.
- 52 isPartOf proceedings.
- 52 keyword "Evaluation Measures".
- 52 keyword "Ontology Alignment".
- 52 keyword "Ontology Matching".
- 52 keyword "User Interaction".
- 52 title "Towards Evaluating Interactive Ontology Matching Tools".
- authorList type List.
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- item-1 type ListItem.
- item-1 hasContent heiko-paulheim.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent sven-hertling.
- item-2 next item-3.
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- item-3 type ListItem.
- item-3 hasContent dominique-ritze.
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- 66 creator kaarel-kaljurand.
- 66 creator tobias-kuhn.
- 66 type InProceedings.
- 66 label "Multilingual semantic wiki based on Attempto Controlled English and Grammatical Framework".
- 66 sameAs 66.
- 66 abstract "We describe a semantic wiki system with an underlying controlled natural language grammar implemented in Grammatical Framework. The grammar restricts the wiki users into a well-defined subset of Attempto Controlled English (ACE) making the wiki content automatically translatable into the Web Ontology Language (OWL) to enable automatic reasoning over the wiki content. Additionally, the grammar facilitates a precise bidirectional automatic translation between ACE and language fragments of a number of other natural languages, to provide a multilingual interface to the wiki. The developed wiki environment thus allows users to build, query and view OWL knowledge bases via a user-friendly multilingual natural language interface. The underlying multilingual grammar is integrated into the wiki itself and can be collaboratively edited to extend the vocabulary of the wiki and modify its multilingual interface. This work demonstrates the combination of the existing technologies of Attempto Controlled English and Grammatical Framework, and is implemented as an extension of the existing ACE-based semantic wiki engine AceWiki.".
- 66 hasAuthorList authorList.
- 66 isPartOf proceedings.
- 66 keyword "Attempto Controlled English".
- 66 keyword "Grammatical Framework".
- 66 keyword "controlled natural language".
- 66 keyword "multilinguality".
- 66 keyword "semantic wiki".
- 66 title "Multilingual semantic wiki based on Attempto Controlled English and Grammatical Framework".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
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- item-1 type ListItem.
- item-1 hasContent kaarel-kaljurand.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent tobias-kuhn.
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- 68 creator ansgar-scherp.
- 68 creator malte-knauf.
- 68 creator stefan-scheglmann.
- 68 creator thomas-gottron.
- 68 type InProceedings.
- 68 label "A Systematic Investigation of Explicit and Implicit Schema Information on the Linked Open Data Cloud".
- 68 sameAs 68.
- 68 abstract "Schema information about resources in the Linked Open Data (LOD) cloud can be provided in a twofold way: it can be explicitly defined by attaching RDF types to the resources. Or it is provided implicitly via the definition of the resources’ properties. In this paper, we analyse the information theoretic proper- ties and the correlation between the two manifestations of schema information. To this end, we have extracted schema information regarding the types and prop- erties defined in the datasets segments provided for the Billion Triples Challenge 2012. We have conducted an in depth analysis and have computed various entropy measures as well as the mutual information encoded in the two types of schema information. Our analysis provides insights into the information encoded in the different schema characteristics. Two major findings are that implicit schema in- formation is far more discriminative and that a schema based on either types or properties alone will only capture between 63.5% and 88.1% of the schema infor- mation contained in the data. Based on these observations, we derive conclusions about the design of future schemas for LOD as well as potential application sce- narios.".
- 68 hasAuthorList authorList.
- 68 isPartOf proceedings.
- 68 keyword "entropy".
- 68 keyword "linked open data".
- 68 keyword "mutual information".
- 68 keyword "schema".
- 68 title "A Systematic Investigation of Explicit and Implicit Schema Information on the Linked Open Data Cloud".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasItem item-3.
- authorList hasItem item-4.
- authorList hasLastItem item-4.
- item-1 type ListItem.
- item-1 hasContent thomas-gottron.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent malte-knauf.
- item-2 next item-3.
- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent stefan-scheglmann.
- item-3 next item-4.
- item-3 previous item-2.
- item-4 type ListItem.
- item-4 hasContent ansgar-scherp.
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- 78 creator axel-cyrille-ngonga-ngomo.
- 78 creator erhard-rahm.
- 78 creator lars-kolb.
- 78 creator michael-hartung.
- 78 creator norman-heino.
- 78 creator soeren-auer.
- 78 type InProceedings.
- 78 label "When to Reach for the Cloud: Using Parallel Hardware for Link Discovery".
- 78 sameAs 78.
- 78 abstract "With the ever-growing amount of RDF data available across the Web, the discovery of links across datasets and deduplication of resources within knowledge bases have become tasks of central importance. Over the last years, several link discovery approaches have been developed to tackle the runtime and complexity problems that are intrinsic to link discovery. Yet, so far, the management of hardware resources for the execution of link discovery tasks has been payed little attention to. This paper aims to address exactly this research gap by investigating the use of hardware resources for link discovery. We implement the HR3 approach within three different paradigms of parallel computing. Based on a comparison of the runtimes of three different implementations, we address the following question: Under which conditions should which hardware be used to link or deduplicate knowledge bases? Our results show that certain tasks that seem to be predestined to being carried out in the cloud can actually be ran using standard massively parallel hardware. Moreover, our evaluation provides break-even points that can serve as guidelines for deciding on when to use which hardware for link discovery.".
- 78 hasAuthorList authorList.
- 78 isPartOf proceedings.
- 78 keyword "Cloud computing".