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- 199 hasAuthorList authorList.
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- 199 keyword "semantic web".
- 199 title "Using Semantics for Automating the Authentication of Web APIs".
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- item-1 hasContent maria-maleshkova.
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- item-2 hasContent carlos-pedrinaci.
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- item-5 hasContent ivan-martinez.
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- 209 creator fabio-ciravegna.
- 209 creator neil-ireson.
- 209 type InProceedings.
- 209 label "Toponym Resolution in Social Media".
- 209 sameAs 209.
- 209 abstract "Increasingly user-generated content is being utilised as a source of information, however each individual piece of content tends to contain low levels of information. In addition, such information tends to be informal and imperfect in nature; containing imprecise, subjective, ambiguous expressions. However the content does not have to be interpreted in isolation as it is linked, either explicitly or implicitly, to a network of interrelated content; it may be grouped or tagged with similar content, comments may be added by other users or it may be related to other content posted at the same time or by the same author or members of the author's social network. This paper generally examines how ambiguous concepts within user-generated content can be assigned a specific/formal meaning by considering the expanding context of the information, i.e. other information contained within directly or indirectly related content, and specifically considers the issue of toponym resolution of locations.".
- 209 hasAuthorList authorList.
- 209 isPartOf proceedings.
- 209 keyword "concept disambiguation".
- 209 keyword "information extraction".
- 209 keyword "semantic web".
- 209 keyword "social networks".
- 209 title "Toponym Resolution in Social Media".
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- item-1 hasContent neil-ireson.
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- 218 creator amit-sheth.
- 218 creator kunal-verma.
- 218 creator pascal-hitzler.
- 218 creator peter-z-yeh.
- 218 creator prateek-jain.
- 218 type InProceedings.
- 218 label "Ontology Alignment for Linked Open Data".
- 218 sameAs 218.
- 218 abstract "The Web of Data currently coming into existence through the Linked Open Data (LOD) effort is a major milestone in realizing the Semantic Web vision. However, the development of applications based on LOD faces difficulties due to the fact that the different LOD datasets are rather loosely connected pieces of information. In particular, links between LOD datasets are almost exclusively on the level of instances, and schema-level information is being ignored. In this paper, we therefore present a system for finding schema-level links between LOD datasets in the sense of ontology alignment. Our system, called BLOOMS, is based on the idea of bootstrapping information already present on the LOD cloud. We also present a comprehensive evaluation which shows that BLOOMS outperforms state-of-the-art ontology alignment systems on LOD datasets. At the same time, BLOOMS is also competitive compared with these other systems on the Ontology Evaluation Alignment Initiative Benchmark datasets.".
- 218 hasAuthorList authorList.
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- 218 keyword "semantic web".
- 218 title "Ontology Alignment for Linked Open Data".
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- item-1 hasContent prateek-jain.
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- item-3 hasContent amit-sheth.
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- 219 creator jan-dedek.
- 219 type InProceedings.
- 219 label "Towards Semantic Annotation Supported by Dependency Linguistics and ILP".
- 219 sameAs 219.
- 219 abstract "In this paper we present a method for semantic annotation of texts, which is based on a deep linguistic analysis (DLA) and Inductive Logic Programming (ILP). The combination of DLA and ILP have following benefits: Manual selection of learning features is not needed. The learning procedure has full available linguistic information at its disposal and it is capable to select relevant parts itself. Learned extraction rules can be easily visualized, understood and adapted by human. A description, implementation and initial evaluation of the method are the main contributions of the paper.".
- 219 hasAuthorList authorList.
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