Matches in ScholarlyData for { ?s ?p ?o. }
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- 89 creator tuukka-ruotsalo.
- 89 type InProceedings.
- 89 label "Domain Specific Data Retrieval on the Semantic Web".
- 89 sameAs 89.
- 89 abstract "The Web content no longer consists of only general text documents, but increasingly structure domain specific data published in the Linked Open Data (LOD) cloud. Data collections in this cloud are, by definition, from dif- ferent domains and indexed with domain specific ontologies and schemas. Such data representation requires retrieval methods that can operate on structured data and semantic feature spaces and remain effective even for small domain specific collections. Unlike previous research, that has concentrated on extending text search by using ontologies as a source for query expansion, we introduce a re- trieval framework based on the well known vector space model of information retrieval to fully support retrieval for Semantic Web data described in Resource Description Framework (RDF) language. We propose an indexing structure, a ranking method, and a way to incorporate reasoning and query expansion in the framework. We evaluate the approach in ad-hoc search using a cultural heritage data collection. Compared to a baseline, experimental results show up to 77% improvement when a combination of reasoning and query expansion is used.".
- 89 hasAuthorList authorList.
- 89 isPartOf proceedings.
- 89 keyword "Domain Specific Data Retrieval".
- 89 keyword "Query expansion".
- 89 keyword "Semantic Web".
- 89 keyword "Semantic search".
- 89 keyword "Web Data Retrieval".
- 89 title "Domain Specific Data Retrieval on the Semantic Web".
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- item-1 hasContent tuukka-ruotsalo.
- 118 creator axel-polleres.
- 118 creator stefan-bischof.
- 118 type InProceedings.
- 118 label "Querying RDFS with Attribute Equations via SPARQL Rewriting".
- 118 sameAs 118.
- 118 abstract "We introduce a technique to determine implicit information in an RDF graph. In addition to taxonomic knowledge about concepts and properties typically expressible in languages such as RDFS and OWL, we focus on knowledge determined by arithmetic equations. The main use case is exploiting knowledge about functional dependencies among numerical properties expressible by means of such arithmetic equations. While some of this knowledge is expressible for instance in rule extensions to ontology languages, we provide a more flexible framework that treats property equations as first class citizens in the ontology language. The combination of ontological reasoning and property equations is realized by extending query rewriting techniques already successfully applied for ontology languages such as (the DL-fragment of) RDFS, or also OWL QL, respectively. We deploy this technique for rewriting SPARQL queries and discuss the feasibility of alternative implementations, such as rule-based approaches.".
- 118 hasAuthorList authorList.
- 118 isPartOf proceedings.
- 118 keyword "SPARQL".
- 118 keyword "equations".
- 118 keyword "query rewriting".
- 118 title "Querying RDFS with Attribute Equations via SPARQL Rewriting".
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- item-1 hasContent axel-polleres.
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- item-2 hasContent stefan-bischof.
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- 130 creator alberto-lavelli.
- 130 creator alessio-palmero-aprosio.
- 130 creator claudio-giuliano.
- 130 type InProceedings.
- 130 label "Automatic expansion of DBpedia exploiting Wikipedia cross-language information".
- 130 sameAs 130.
- 130 abstract "DBpedia is a project aiming to represent Wikipedia content in RDF triples. It plays a central role in the Semantic Web, due to the large and growing number of resources linked to it. Nowadays, the English version covers around 1.7M Wikipedia pages, although the English Wikipedia contains almost 4M pages, showing a clear problem of coverage. In other languages (like French and Spanish) the coverege is even lower. The objective of this paper is to define a methodology to increase the coverage of DBpedia in different languages. The major problems that we have to solve concern the high number of classes involved in the DBpedia ontology and the lack of coverage for some classes in certain languages. In order to deal with these problems, we first extend the population of the classes for the different languages by connecting the corresponding Wikipedia pages through cross-language links. Then, we train a supervised classifier using this extended set as training data. We evaluated our system using a manually annotated test set, demonstrating that our approach can add around 1.7M new entities to DBpedia with high precision (90%) and recall (50%). The resulting resource will be made available through a SPARQL endpoint and a downloadable package.".
- 130 hasAuthorList authorList.
- 130 isPartOf proceedings.
- 130 keyword "DBpedia".
- 130 keyword "Linked Open Data".
- 130 keyword "Machine learning".
- 130 keyword "Ontology population".
- 130 keyword "Semantic Web".
- 130 title "Automatic expansion of DBpedia exploiting Wikipedia cross-language information".
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- item-1 hasContent alessio-palmero-aprosio.
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- item-2 hasContent claudio-giuliano.
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- item-3 hasContent alberto-lavelli.
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- 156 creator claudia-wagner.
- 156 creator markus-strohmaier.
- 156 creator matthew-rowe.
- 156 type InProceedings.
- 156 label "Measuring the Topical Specificity of Online Communities".
- 156 sameAs 156.
- 156 abstract "For community managers and hosts it is not only important to identify the current key topics of a community but also to assess the specificity level of the community for: a) creating sub-communities, and: b) anticipating community behaviour and topical evolution. In this paper we present an approach that empirically characterises the topical specificity of online community forums by measuring the abstraction of semantic concepts discussed within such forums. We present a range of concept abstraction measures that function over concept graphs - i.e. resource type-hierarchies and SKOS category structures - and demonstrate the efficacy of our method with an empirical evaluation using a ground truth ranking of forums. Our results show that the proposed approach outperforms a random baseline and that resource type-hierarchies work well when predicting the topical specificity of any forum with various abstraction measures.".
- 156 hasAuthorList authorList.
- 156 isPartOf proceedings.
- 156 keyword "concept graphs".
- 156 keyword "data mining".
- 156 keyword "online communities".
- 156 keyword "topical specificity".
- 156 title "Measuring the Topical Specificity of Online Communities".
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- item-1 hasContent matthew-rowe.
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- item-2 hasContent claudia-wagner.
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