The BBC World Service Archive prototype

Raimond, Yves; Ferne, Tristan; Smethurst, Michael; Adams, Gareth

doi:10.1016/j.websem.2014.07.005

Cited by 14 publications

(3 citation statements)

References 11 publications

(14 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Third, it allows us to exploit the cognitive diversity of collective intelligence. This vision may be applied to a wide range of application domains (e. g. literature management (Morishima et al, 2012), urban and geospatial systems (Celino et al, 2012b;Atzmueller et al, 2014), the media sector (Raimond et al, 2014) and the medical domain (Mortensen et al, 2013a)). …”

Section: Crowdsourcing For the Semantic Webmentioning

confidence: 99%

Crowdsourcing and the Semantic Web: A Research Manifesto

Sarasua

Simperl

Noy

et al. 2015

HCj

View full text Add to dashboard Cite

Our goal with this research manifesto is to define a roadmap to guide the evolution of the new research field that is emerging at the intersection between crowdsourcing and the Semantic Web. We analyze the confluence of these two disciplines by exploring their relationship. First, we focus on how the application of crowdsourcing techniques can enhance the machine-driven execution of Semantic Web tasks. Second, we look at the ways in which machine-processable semantics can benefit the design and management of crowdsourcing projects. As a result, we are able to describe a list of successful or promising scenarios for both perspectives, identify scientific and technological challenges, and compile a set of recommendations to realize these scenarios effectively. This research manifesto is an outcome of the Dagstuhl Seminar 14282: Crowdsourcing and the Semantic Web.

show abstract

Section: Crowdsourcing For the Semantic Webmentioning

confidence: 99%

Crowdsourcing and the Semantic Web: A Research Manifesto

Sarasua

Simperl

Noy

et al. 2015

HCj

View full text Add to dashboard Cite

show abstract

“…Knowledge graphs allow integrating heterogeneous data to make decisions, provide recommendations or deduct new knowledge. Knowledge graphs are leveraged in different domains, e.g., media [111], government [117,62], search engines [121,118], commerce [80,106], social networks [103,58], etc.…”

Section: Introductionmentioning

confidence: 99%

Declarative RDF graph generation from heterogeneous (semi-)structured data: A systematic literature review

Assche

Delva

Haesendonck

et al. 2023

Journal of Web Semantics

View full text Add to dashboard Cite

“…These graphs are generally large and cover multiple domains. The second type focuses on describing a particular field of interest, for example, academic literature publication (e.g., OpenCitations [4], SciGraph [5], Microsoft Academic Knowledge Graph [6]), geographic (e.g., LinkedGeoData [7]), life sciences (e.g., Bio2RDF [8]), media (e.g., the BBC World Service Archive [9]), and can effectively support knowledge retrieval and reasoning for different applications [10,11].…”

Section: Introductionmentioning

confidence: 99%

Knowledge Graph Engineering Based on Semantic Annotation of Tables

Dorodnykh,

Yurin

2023

Computation

View full text Add to dashboard Cite

A table is a convenient way to store, structure, and present data. Tables are an attractive knowledge source in various applications, including knowledge graph engineering. However, a lack of understanding of the semantic structure and meaning of their content may reduce the effectiveness of this process. Hence, the restoration of tabular semantics and the development of knowledge graphs based on semantically annotated tabular data are highly relevant tasks that have attracted a lot of attention in recent years. We propose a hybrid approach using heuristics and machine learning methods for the semantic annotation of relational tabular data and knowledge graph populations with specific entities extracted from the annotated tables. This paper discusses the main stages of the approach, its implementation, and performance testing. We also consider three case studies for the development of domain-specific knowledge graphs in the fields of industrial safety inspection, labor market analysis, and university activities. The evaluation results revealed that the application of our approach can be considered the initial stage for the rapid filling of domain-specific knowledge graphs based on tabular data.

show abstract

The BBC World Service Archive prototype

Cited by 14 publications

References 11 publications

Crowdsourcing and the Semantic Web: A Research Manifesto

Crowdsourcing and the Semantic Web: A Research Manifesto

Declarative RDF graph generation from heterogeneous (semi-)structured data: A systematic literature review

Knowledge Graph Engineering Based on Semantic Annotation of Tables

Contact Info

Product

Resources

About