Weiqin Xu's research while affiliated with Centre Hospitalier de Marne-la-Vallée and other places

Publications (6)

Preprint
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One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is that of a: "Public FAIR Knowledge Graph of Everything: We increasingly see the creation of knowledge graphs that capture information about the entirety of a class of ent...
Preprint
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Edge computing emerges as an innovative platform for services requiring low latency decision making. Its success partly depends on the existence of efficient data management systems. We consider that knowledge graph management systems have a key role to play in this context due to their data integration and reasoning features. In this paper, we pre...
Chapter
In this paper, we extend LiteMat, an RDFS and owl:sameAs inference-enabled RDF encoding scheme, which is used in a distributed knowledge graph data management system. Our extensions enable to reach RDFS++ expressiveness by integrating owl:transitiveProperty and owl:inverseOf properties. Considering the latter, owl:inverseOf property, we propose a s...
Preprint
Full-text available
Crowd-sourced knowledge graphs are subject to contain implicit biased information. Statement can be both true and false at the same time, depending on who has to judge the statement. In this work, we present a four-step human-in-the-loop framework to handle implicit bias in knowledge graphs. The steps are collection, analysis, review and refinement...

Citations

... SuccinctEdge's reasoning services are based on the LiteMat encoding solution [4]. This approach prevents inference materialization and reduces the cost of the SPARQL query rewriting task, the two most frequent reasoning solutions in RDF stores. ...