Matches in ScholarlyData for { ?s ?p ?o. }
- 4 type InProceedings.
- 4 label "Zhi# - OWL Aware Compilation".
- 4 sameAs 4.
- 4 abstract "The usefulness of the Web Ontology Language to describe domains of discourse and to facilitate automatic reasoning services has been widely acknowledged. However, the programmability of ontological knowledge bases is severely impaired by the different conceptual bases of statically typed object-oriented programming languages such as Java and C# and ontology languages such as the Web Ontology Language (OWL). In this work, a novel programming language is presented that integrates OWL and XSD data types with C#. The Zhi# programming language is the first solution of its kind to make XSD data types and OWL class descriptions first-class citizens of a widely-used programming language. The Zhi# programming language eases the development of Semantic Web applications and facilitates the use and reuse of knowledge in form of ontologies. The presented approach was successfully validated to reduce the number of possible runtime errors compared to the use of XML and OWL APIs.".
- 4 hasAuthorList authorList.
- 4 isPartOf proceedings.
- 4 keyword "C#".
- 4 keyword "OWL DL".
- 4 keyword "Zhi#".
- 4 keyword "ontologies".
- 4 keyword "programmability".
- 4 title "Zhi# - OWL Aware Compilation".
- 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 alexander-paar.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent denny-vrandecic.
- item-2 previous item-1.
- 5 creator luis-m-vilches-blazquez.
- 5 creator oscar-corcho.
- 5 creator victor-saquicela.
- 5 type InProceedings.
- 5 label "Lightweight Semantic Annotation of Geospatial RESTful Services".
- 5 sameAs 5.
- 5 abstract "RESTful services are increasingly gaining traction over WS-* ones. As with WS-* services, their semantic annotation can provide benefits in tasks related to their discovery, composition and mediation. In this paper we present an approach to automate the semantic annotation of RESTful services using a cross-domain ontology, two semantic resources like DBpedia and GeoNames, and additional external resources (suggestion and synonym services). We also present a preliminary evaluation in the geospatial domain that proves the feasibility of our approach in a domain where RESTful services are increasingly appearing and highlights that it is possible to carry out this semantic annotation with satisfactory results.".
- 5 hasAuthorList authorList.
- 5 isPartOf proceedings.
- 5 keyword "Geospatial RESTful services".
- 5 keyword "REST".
- 5 keyword "Semantic annotation".
- 5 title "Lightweight Semantic Annotation of Geospatial RESTful Services".
- 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 victor-saquicela.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent luis-m-vilches-blazquez.
- item-2 next item-3.
- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent oscar-corcho.
- item-3 previous item-2.
- 12 creator fabian-abel.
- 12 creator geert-jan-houben.
- 12 creator ke-tao.
- 12 creator qi-gao.
- 12 type InProceedings.
- 12 label "Semantic Enrichment of Twitter Posts for User Profile Construction".
- 12 sameAs 12.
- 12 abstract "As the most popular microblogging platform, the vast amount of content on Twitter is constantly growing so that the retrieval of relevant information (streams) is becoming more and more difficult every day. Representing the semantics of individual Twitter activities and modeling the interests of Twitter users would allow for personalization and therewith countervail the information overload. Given the variety of topics people discuss on Twitter, semantic user profiles generated from Twitter posts moreover promise to be beneficial also for other applications on the Social Web. However, automatically inferring the semantic meaning of tweets is a non-trivial problem. In this paper we investigate semantic user modeling based on Twitter activities. We introduce and analyze methods for linking Twitter posts with related news articles in order to contextualize Twitter activities. We then propose and compare strategies that exploit the semantics extracted from both tweets and related news articles to represent individual Twitter activities in a semantically meaningful way. A large-scale evaluation validates the applicability of our approach and shows that our methods relate tweets to news articles with high precision, enrich the semantics of tweets clearly and have tremendous impact on the construction of semantic user profiles for the Social Web.".
- 12 hasAuthorList authorList.
- 12 isPartOf proceedings.
- 12 keyword "news".
- 12 keyword "semantic enrichment".
- 12 keyword "social web".
- 12 keyword "twitter".
- 12 keyword "user profile construction".
- 12 title "Semantic Enrichment of Twitter Posts for User Profile Construction".
- 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 qi-gao.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent fabian-abel.
- item-2 next item-3.
- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent ke-tao.
- item-3 next item-4.
- item-3 previous item-2.
- item-4 type ListItem.
- item-4 hasContent geert-jan-houben.
- item-4 previous item-3.
- 14 creator conor-hayes.
- 14 creator john-breslin.
- 14 creator mengjiao-wang.
- 14 creator sheila-kinsella.
- 14 type InProceedings.
- 14 label "Improving Categorisation in Social Media using Hyperlinks to Structured Data Sources".
- 14 sameAs 14.
- 14 abstract "Social media presents unique challenges for topic classification, including the brevity of posts, the informal nature of conversations, and the frequent reliance on external hyperlinks to give context to a conversation. In this paper we investigate the usefulness of these external hyperlinks for determining the topic of individual posts. We focus our analysis on objects which have related metadata available on the Web, either via APIs or as Linked Data. Our experiments show that the inclusion of metadata from hyperlinked objects in addition to the original post content significantly improved classifier performance on two disparate datasets. We found that including selected metadata from APIs and Linked Data gave better results than including text from HTML pages. We also make use of the semantics of the data to compare the usefulness of different types of external metadata for topic classification in a social media dataset.".
- 14 hasAuthorList authorList.
- 14 isPartOf proceedings.
- 14 keyword "Linked Data".