Matches in ScholarlyData for { ?s ?p ?o. }
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- item-2 hasContent matthias-knorr.
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- item-3 hasContent joao-leite.
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- paper-13 type InProceedings.
- paper-13 label "On the Semantics of R2RML and its Relationship with the Direct Mapping".
- paper-13 sameAs paper-13.
- paper-13 abstract "The W3C Relational Database to RDF (RDB2RDF) standards are positioned to bridge the gap between Relational Databases and the Semantic Web. The standards consist of two interrelated and complementary specifications: “Direct Mapping of Relational Data to RDF” and “R2RML: RDB to RDF Mapping Language”. In this paper we present initial results on the formal study of the R2RML mapping language by defining its semantics using Datalog. We prove that there are a total of 57 distinct Datalog rules which can be used to generate RDF triples from a relational table. Additionally, we provide insights on the relationship between R2RML and Direct Mapping.".
- paper-13 hasAuthorList authorList.
- paper-13 isPartOf poster-demo-proceedings.
- paper-13 title "On the Semantics of R2RML and its Relationship with the Direct Mapping".
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- item-1 hasContent juan-sequeda.
- paper-14 type InProceedings.
- paper-14 label "An FCA Framework for Knowledge Discovery in SPARQL Query Answers".
- paper-14 sameAs paper-14.
- paper-14 abstract "Formal concept analysis (FCA) is used for knowledge discovery within data. In FCA, concept lattices are very good tools for classification and organization of data, hence, they enable the user to visualize the answers of its SPARQL query as concept lattices instead of the usual answer formats such as: RDF/XML, JSON, CSV, and HTML. Consequently, in this work, we apply FCA to reveal hidden relations within SPARQL query answers by means of concept lattices.".
- paper-14 hasAuthorList authorList.
- paper-14 isPartOf poster-demo-proceedings.
- paper-14 title "An FCA Framework for Knowledge Discovery in SPARQL Query Answers".
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- item-1 hasContent melisachew-wudage-chekol.
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- item-2 hasContent amedeo-napoli.
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- paper-15 type InProceedings.
- paper-15 label "A Study on the Correspondence between FCA and $\mathcal{ELI}$ Ontologies".
- paper-15 sameAs paper-15.
- paper-15 abstract "The description logic $\mathcal{EL}$ has been used to support ontology design in various domains, and especially in biology and medecine. $\mathcal{EL}$ is known for its efficient reasoning and query answering capabilities. By contrast, ontology design and query answering can be supported and guided within an FCA framework. Accordingly, in this paper, we propose a formal transformation of $\mathcal{ELI}$ (an extension of $\mathcal{EL}$ with \textit{inverse roles}) ontologies into an FCA framework, i.e. $K_\mathrm{\mathcal{ELI}}$, and we provide a formal characterization of this transformation. Then we show that SPARQL query answering over $\mathcal{ELI}$ ontologies can be reduced to lattice query answering over $K_\mathrm{\mathcal{ELI}}$ concept lattices. This simplifies the query answering task and shows that some basic semantic web tasks can be improved when considered from an FCA perspective.".
- paper-15 hasAuthorList authorList.
- paper-15 isPartOf poster-demo-proceedings.
- paper-15 title "A Study on the Correspondence between FCA and $\mathcal{ELI}$ Ontologies".
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- item-1 hasContent melisachew-wudage-chekol.
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- paper-16 type InProceedings.
- paper-16 label "Using Ontologies to Identify Patients with Diabetes in Electronic Health Records".
- paper-16 sameAs paper-16.
- paper-16 abstract "This paper describes a work in progress that explores the applicability of ontology for providing solutions in medical domain. We investigate whether it is feasible to use ontologies and ontology-based data access to automate one of common clinical tasks that are constantly faced by general practitioners but labor intensive and error prone in term of relevant information retrieved from electronic health records. The focus of our study is on improving diabetes patient selection for clinical trials or medical research. The biggest impediment to automating such clinical tasks is the essential requirement of bridging the semantic gaps between existing patient data from electronic health records, such as reasons for visit, chronic conditions and diagnoses from practice notes, pathology tests and prescriptions stored in general practice information systems, and the ways which researchers or general practitioners interpret those records. Our current comprehension is that automation of identifying diabetes patients for clinical or research purposes can be specified systematically as a solution supported by semantic retrieval. We detail the challenges to build a realistic case study, which consists of solving issues related to conceptualization of data and domain context, integration of different datasets, ontology creation based on SNOMED CT-AU® standard, mapping between existing data and ontology, and dilemma of data fitness for research use. Our prototype is based on data which scale to thirteen years of approximate 100,000 anonymous patient records from four general practices in south western Sydney.".
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- paper-16 title "Using Ontologies to Identify Patients with Diabetes in Electronic Health Records".
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- item-1 hasContent hairong-yu.
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- item-2 hasContent siaw-teng-liaw.
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- item-3 hasContent jane-taggart.
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- item-4 hasContent alireza-rahimi.
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- paper-17 type InProceedings.
- paper-17 label "Towards Semantic Annotations of Web Tables".
- paper-17 sameAs paper-17.
- paper-17 abstract "Web tables comprise a rich source of factual information.However, without semantic annotation of the tables’ content the infor-mation is not usable for automatic integration and search. We propose amethodology to annotate table headers with semantic type informationbased on the content of column’s cells. In our experiments on 50 tableswe achieved an F1 value of 0.55, where the accuracy greatly varies de-pending on the used ontology. Regarding computational complexity wefound out that 94% of the maximal F1 score on average 20 cells (37%)need to be considered. Results suggest that the choice of the ontologyplays a more crucial role for type inference than the number of cells used.".
- paper-17 hasAuthorList authorList.
- paper-17 isPartOf poster-demo-proceedings.
- paper-17 title "Towards Semantic Annotations of Web Tables".
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