Matches in ScholarlyData for { ?s ?p ?o. }
- 15 keyword "Named Entity Extraction".
- 15 keyword "Speech Processing".
- 15 keyword "Text Processing".
- 15 title "Automated interlinking of speech radio archives".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasLastItem item-2.
- item-1 type ListItem.
- item-1 hasContent yves-raimond.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent chris-lowis.
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- 21 creator christoph-boehm.
- 21 creator felix-naumann.
- 21 creator toni-gruetze.
- 21 type InProceedings.
- 21 label "Holistic and Scalable Ontology Alignment for Linked Open Data".
- 21 sameAs 21.
- 21 abstract "The Linked Open Data community continuously releases massive amounts of RDF data that shall be used to easily create applications that incorporate data from different sources. Inter-operability across different sources requires links at instance- and at schema-level, thus connecting entities on the one hand and relating concepts on the other hand. State-of-the-art entity- and ontology-alignment methods produce high quality alignments for two source ontologies, whereas an identification of relevant and meaningful pairs of ontologies is a precondition. Therefore, these methods lack in dealing with heterogeneous web data from many sources simultaneously, e.g., data from a web crawl. To this end we propose Holistic Concept Matching (HCM). HCM aligns thousands of concepts from hundreds of ontologies (from many sources) simultaneously, while maintaining scalability and leveraging the global view on the entire data cloud. We evaluated our approach against the OAEI ontology alignment benchmark as well as the 2011 Billion Triple Challenge data and present high precision results.".
- 21 hasAuthorList authorList.
- 21 isPartOf proceedings.
- 21 keyword "LOD".
- 21 keyword "ontology alignment".
- 21 keyword "scalability".
- 21 title "Holistic and Scalable Ontology Alignment for Linked Open Data".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasItem item-3.
- authorList hasLastItem item-3.
- item-1 type ListItem.
- item-1 hasContent toni-gruetze.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent christoph-boehm.
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- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent felix-naumann.
- item-3 previous item-2.
- 26 creator gary-wills.
- 26 creator mike-wald.
- 26 creator nigel-r-shadbolt.
- 26 creator tope-omitola.
- 26 creator yunjia-li.
- 26 type InProceedings.
- 26 label "Synote: Weaving Media Fragments and Linked Data".
- 26 sameAs 26.
- 26 abstract "While end users could easily share and tag the multimedia resources online, the searching and reusing of the inside content of multimedia, such as a certain area within an image or a ten minutes segment within a one-hour video, is still difficult. Linked data is a promising way to interlink media fragments with other resources. Many applications in Web 2.0 have generated large amount of external annotations linked to media fragments. In this paper, we use Synote as the target application to discuss how media fragments could be published together with external annotations following linked data principles. Our design solves the dereferencing, describing and interlinking methods problems in interlinking multimedia. We also implement a model to let Google index media fragments which improves media fragments' online presence. The evaluation shows that our design can successfully publish media fragments for semantic Web agent and traditional search engine. Publishing media fragments, using the design we describe in this paper, will lead to better indexing of multimedia resources and their consequent findability and reuse.".
- 26 hasAuthorList authorList.
- 26 isPartOf proceedings.
- 26 keyword "annotation".
- 26 keyword "linked data".
- 26 keyword "media fragment".
- 26 keyword "schema.org".
- 26 keyword "search".
- 26 title "Synote: Weaving Media Fragments and Linked Data".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasItem item-3.
- authorList hasItem item-4.
- authorList hasItem item-5.
- authorList hasLastItem item-5.
- item-1 type ListItem.
- item-1 hasContent yunjia-li.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent mike-wald.
- item-2 next item-3.
- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent tope-omitola.
- item-3 next item-4.
- item-3 previous item-2.
- item-4 type ListItem.
- item-4 hasContent nigel-r-shadbolt.
- item-4 next item-5.
- item-4 previous item-3.
- item-5 type ListItem.
- item-5 hasContent gary-wills.
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- 27 creator andreas-schultz.
- 27 creator carlos-r-rivero.
- 27 creator christian-bizer.
- 27 creator david-ruiz.
- 27 type InProceedings.
- 27 label "Benchmarking the Performance of Linked Data Translation Systems".
- 27 sameAs 27.
- 27 abstract "Linked Data sources on theWeb use a wide range of different vocabularies to represent the same type of entity. For some types of entities, like people or bibliographic record, common vocabularies have emerged that are used by multiple data sources. But even for representing data of these common types, different user communities use different competing common vocabularies. Linked Data applications that want to understand as much data from the Web as possible, thus need to overcome the vocabulary heterogeneity and translate the original data into a single target vocabulary. To support application developers with this integration task, several Linked Data translation systems have been developed. These systems provide languages to represent correspondences in the form of declarative mappings and use these mappings to translate heterogeneous Web data into a single target vocabulary.In this paper, we present a benchmark for comparing the expressivity as well as the runtime performance of data translation systems. Based on a set of examples from the LOD Cloud, we developed a catalog of fifteen data translation patterns and survey how often these patterns occur in our example set. Based on these statistics, we designed the LODIB (Linked Open Data Integration Benchmark) which aims to reflect the real-world heterogeneities that exist on the Web of Data. We apply the benchmark to test the performance of two data translation systems, Mosto and LDIF, and compare the performance of the systems with the SPARQL CONSTRUCT performance of the Jena TDB RDF store.".
- 27 hasAuthorList authorList.
- 27 isPartOf proceedings.
- 27 keyword "Benchmarking".
- 27 keyword "Data translation".
- 27 keyword "Linked Data".