Matches in ScholarlyData for { ?s ?p ?o. }
- 125 title "Quality Assessment of Linked Datasets using Probabilistic Approximations".
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- item-1 hasContent jeremy-debattista.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent santiago-londono.
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- item-3 hasContent christoph-lange.
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- item-4 type ListItem.
- item-4 hasContent soeren-auer.
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- 13 creator gerhard-wohlgenannt.
- 13 type InProceedings.
- 13 label "Leveraging and Balancing Heterogeneous Sources of Evidence in Ontology Learning".
- 13 sameAs 13.
- 13 abstract "Ontology learning (OL) aims at the (semi-)automatic acquisition of ontologies from sources of evidence, typically domain text. Recently, there has been a trend towards the application of multiple and heterogeneous evidence sources in OL. Heterogeneous sources provide benefits, such as higher accuracy by exploiting redundancy across evidence sources, and including complementary information. When using evidence sources which are heterogeneous in quality, amount of data provided and type, then a number of questions arise, for example: How many sources are needed to see significant benefits from heterogeneity, what is an appropriate number of evidences per source, is balancing the number of evidences per source important, and to what degree can the integration of multiple sources overcome low quality input of individual sources? This research presents an extensive evaluation based on an existing OL system. It gives answers and insights on the research questions posed for the OL task of concept detection, and provides further hints from experience made. Among other things, our results suggest that a moderate number of evidences per source as well as a moderate number of sources resulting in a few thousand data instances are sufficient to exploit the benefits of heterogeneous evidence integration.".
- 13 hasAuthorList authorList.
- 13 isPartOf proceedings.
- 13 keyword "evidence integration".
- 13 keyword "heterogeneous evidence sources".
- 13 keyword "ontology learning".
- 13 keyword "spreading activation".
- 13 title "Leveraging and Balancing Heterogeneous Sources of Evidence in Ontology Learning".
- authorList type List.
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- item-1 type ListItem.
- item-1 hasContent gerhard-wohlgenannt.
- 132 creator giuseppe-pirro.
- 132 creator olaf-hartig.
- 132 type InProceedings.
- 132 label "A Context-Based Semantics for SPARQL Property Paths over the Web".
- 132 sameAs 132.
- 132 abstract "As of today, there exists no standard language for querying Linked Data on the Web, where navigation across distributed data sources is a key feature. A natural candidate seems to be SPARQL, which recently has been enhanced with navigational capabilities thanks to the introduction of property paths (PPs). However, the semantics of SPARQL restricts the scope of navigation via PPs to single RDF graphs. This restriction limits the applicability of PPs on the Web. To fill this gap, in this paper we provide formal foundations for evaluating PPs on the Web, thus contributing to the definition of a query language for Linked Data. In particular, we introduce a query semantics for PPs that couples navigation at the data level with navigation on the Web graph. Given this semantics we find that for some PP-based SPARQL queries a complete evaluation on the Web is not feasible. To enable systems to identify queries that can be evaluated completely, we establish a syntactic and, thus, decidable property of such queries.".
- 132 hasAuthorList authorList.
- 132 isPartOf proceedings.
- 132 keyword "Linked Data".
- 132 keyword "Navigation".
- 132 keyword "Property Paths".
- 132 keyword "SPARQL".
- 132 keyword "Theory".
- 132 title "A Context-Based Semantics for SPARQL Property Paths over the Web".
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- item-1 hasContent olaf-hartig.
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- item-2 hasContent giuseppe-pirro.
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- 134 creator elena-paslaru-bontas-simperl.
- 134 creator markus-luczak-roesch.
- 134 creator oluwaseyi-feyisetan.
- 134 creator ramine-tinati.
- 134 type InProceedings.
- 134 label "Towards hybrid NER: a study of content and crowdsourcing-related performance factors".
- 134 sameAs 134.
- 134 abstract "This paper explores the factors that influence the performance of hybrid named entity recognition (NER) approaches to microblogs, which combine state-of-the-art automatic techniques with human and crowd computing. We identify a set of content and crowdsourcing-related features (number of entities in a post, types of entities, skipped true-positive posts, average time spent to complete the tasks, and interaction with the user interface) and analyze their impact on the accuracy of the results and the timeliness of their delivery. Using CrowdFlower and a simple, custom built gamified NER tool we run experiments on three datasets from related literature and a fourth newly annotated corpus. Our findings show that crowd workers are adept at recognizing people, locations, and implicitly identified entities within shorter microposts. We expect them to lead to the design of more advanced NER pipelines, informing the way in which tweets are chosen to be outsourced or processed by automatic tools. Experimental results are published as JSON-LD for further use by the research community.".
- 134 hasAuthorList authorList.
- 134 isPartOf proceedings.
- 134 keyword "Crowdsourcing".
- 134 keyword "Microposts".
- 134 keyword "Named entity recognition".
- 134 title "Towards hybrid NER: a study of content and crowdsourcing-related performance factors".
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- item-1 type ListItem.
- item-1 hasContent oluwaseyi-feyisetan.
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- item-2 hasContent markus-luczak-roesch.
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- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent elena-paslaru-bontas-simperl.
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- item-4 type ListItem.
- item-4 hasContent ramine-tinati.
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