Matches in ScholarlyData for { ?s ?p ?o. }
- paper-15 hasAuthorList authorList.
- paper-15 isPartOf proceedings-1.
- paper-15 title "Composition of Linked Data-based RESTful Services".
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- item-1 type ListItem.
- item-1 hasContent steffen-stadtmueller.
- paper-16 type InProceedings.
- paper-16 label "Linked Stream Data Processing Engines: Facts and Figures".
- paper-16 sameAs paper-16.
- paper-16 abstract "Linked Stream Data, i.e., the RDF data model extended for representing stream data generated from sensors social network applications, is gaining popularity. This has motivated considerable work on developing corresponding data models associated with processing engines. However, current implemented engines have not been thoroughly evaluated to assess their capabilities. For reasonable systematic evaluations, in this work we propose a novel, customizable evaluation framework and a corresponding methodology for realistic data generation, system testing, and result analysis. Based on this evaluation environment, extensive experiments have been conducted in order to compare the state-of-the-art LSD engines wrt. qualitative and quantitative properties, taking into account the underlying principles of stream processing. Consequently, we provide a detailed analysis of the experimental outcomes that reveal useful findings for improving current and future engines.".
- paper-16 hasAuthorList authorList.
- paper-16 isPartOf proceedings-1.
- paper-16 title "Linked Stream Data Processing Engines: Facts and Figures".
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- item-1 hasContent danh-le-phuoc.
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- item-2 hasContent minh-dao-tran.
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- item-6 hasContent michael-fink.
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- paper-17 type InProceedings.
- paper-17 label "Evaluation of a layered approach to question answering over linked data".
- paper-17 sameAs paper-17.
- paper-17 abstract "We present a question answering system architecture which processes natural language questions in a pipeline consisting of five steps: i) question parsing and query template generation, ii) lookup in an inverted index, iii) string similarity computation, iv) lookup in a lexical database in order to find synonyms, and v) semantic similarity computation. These steps are ordered with respect to their computational effort, following the idea of layered processing: questions are passed on along the pipeline only if they cannot be answered on the basis of earlier processing steps, thereby invoking computationally expensive operations only for complex queries that require them. In this paper we present an evaluation of the system on the dataset provided by the 2nd Open Challenge on Question Answering over Linked Data (QALD-2). The main, novel contribution is a systematic empirical investigation of the impact of the single processing components on the overall performance of question answering over linked data.".
- paper-17 hasAuthorList authorList.
- paper-17 isPartOf proceedings-1.
- paper-17 title "Evaluation of a layered approach to question answering over linked data".
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- item-1 hasContent sebastian-walter.
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- item-2 hasContent christina-unger.
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- item-4 hasContent daniel-baer.
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- paper-18 type InProceedings.
- paper-18 label "Tag Recommendation for Large-Scale Ontology-Based Information Systems".
- paper-18 sameAs paper-18.
- paper-18 abstract "We tackle the problem of improving the relevance of automatically selected tags in large-scale ontology-based information systems. Contrary to traditional settings where tags can be chosen arbitrarily, we focus on the problem of recommending tags (e.g., concepts) directly from a collaborative, user-driven ontology. We compare the effectiveness of a series of approaches to select the best tags ranging from traditional IR techniques such as TF/IDF weighting to novel techniques based on ontological distances and latent Dirichlet allocation. All our experiments are run against a real corpus of tags and documents extracted from the ScienceWise portal, which is connected to ArXiv.org and is currently used by growing number of researchers. The datasets for the experiments are made available online for reproducibility purposes.".
- paper-18 hasAuthorList authorList.
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- paper-18 title "Tag Recommendation for Large-Scale Ontology-Based Information Systems".
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- item-1 hasContent roman-prokofyev.
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- item-2 hasContent alexey-boyarsky.
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- item-3 hasContent oleg-ruchayskiy.