Add to ORKGAbstract. Annotations obtained by Cultural Heritage institutions from the crowd need to be automatically assessed for their quality. Machine learning using graph kernels is an effective technique to use structural information in datasets to make predictions. We employ the Weisfeiler-Lehman graph kernel for RDF to make predictions about the quality of crowdsourced annotations in Steve.museum dataset, which is modelled and enriched as RDF. Our results indicate that we could predict quality of crowdsourced annotations with an accuracy of 75%. We also employ the kernel to understand which features from the RDF graph are relevant to make predictions about different categories of quality
Over the last decade, hundreds of thousands of volunteers have contributed to science by collecting ...
Data collection by means of crowdsourcing can be costly or produce inaccurate results. Methods have ...
In this paper we introduce a framework for learning from RDF data using graph kernels that count sub...
Annotations obtained by Cultural Heritage institutions from the crowd need to be automatically asses...
Part 2: Full PapersInternational audienceAnnotations obtained by Cultural Heritage institutions from...
\u3cp\u3eAnnotations obtained by Cultural Heritage institutions from the crowd need to be automatica...
Abstract. Cultural heritage institutions are employing crowdsourcing techniques to enrich their coll...
Wikidata is a collaboratively-edited knowledge graph; it expresses knowledge in the form of subject-...
Abstract. Provenance is a domain-independent means to represent what happened in an application, whi...
With crowdsourcing systems, labels can be obtained with low cost, which facilitates the creation of ...
Crowdsourcing is leveraged to rapidly and inexpensively collect annotations, but concerns have been ...
Provenance is a domain-independent means to represent what happened in an application, which can hel...
Understanding the dynamics of a crowdsourcing application and controlling the quality of the data it...
The creation of golden standard datasets is a costly business. Optimally more than one judgment per ...
Abstract—Given a topic and its top-k most relevant words generated by a topic model, how can we tell...
Over the last decade, hundreds of thousands of volunteers have contributed to science by collecting ...
Data collection by means of crowdsourcing can be costly or produce inaccurate results. Methods have ...
In this paper we introduce a framework for learning from RDF data using graph kernels that count sub...
Annotations obtained by Cultural Heritage institutions from the crowd need to be automatically asses...
Part 2: Full PapersInternational audienceAnnotations obtained by Cultural Heritage institutions from...
\u3cp\u3eAnnotations obtained by Cultural Heritage institutions from the crowd need to be automatica...
Abstract. Cultural heritage institutions are employing crowdsourcing techniques to enrich their coll...
Wikidata is a collaboratively-edited knowledge graph; it expresses knowledge in the form of subject-...
Abstract. Provenance is a domain-independent means to represent what happened in an application, whi...
With crowdsourcing systems, labels can be obtained with low cost, which facilitates the creation of ...
Crowdsourcing is leveraged to rapidly and inexpensively collect annotations, but concerns have been ...
Provenance is a domain-independent means to represent what happened in an application, which can hel...
Understanding the dynamics of a crowdsourcing application and controlling the quality of the data it...
The creation of golden standard datasets is a costly business. Optimally more than one judgment per ...
Abstract—Given a topic and its top-k most relevant words generated by a topic model, how can we tell...
Over the last decade, hundreds of thousands of volunteers have contributed to science by collecting ...
Data collection by means of crowdsourcing can be costly or produce inaccurate results. Methods have ...
In this paper we introduce a framework for learning from RDF data using graph kernels that count sub...