Object Link Structure in the Semantic Web

Ge, Weiyi; Chen, Jianfeng; Hu, Wei; Qu, Yuzhong

doi:10.1007/978-3-642-13489-0_18

Cited by 25 publications

(19 citation statements)

References 21 publications

(29 reference statements)

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“…The work of Ge et al [24] reports experimental results on analysing the complex network structure of the object link graphs (i.e., the RDF data graph) constructed from two large datasets: 11.7 million RDF documents crawled in 2008 and 21.6 million RDF documents crawled in 2009. Both datasets are crawled by the Falcon-S search engine.…”

Section: Link-structure Analysesmentioning

confidence: 99%

An empirical survey of Linked Data conformance

Hogan

Umbrich

Harth

et al. 2012

Journal of Web Semantics

140

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Section: Link-structure Analysesmentioning

confidence: 99%

An empirical survey of Linked Data conformance

Hogan

Umbrich

Harth

et al. 2012

Journal of Web Semantics

140

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“…In recent work, [8] analysed the "object link graph": the Web of Data restricted to its object-to-object links, i.e. after removing all links from objects to classes, and all class-and property-hierarchies.…”

Section: Related Workmentioning

confidence: 99%

Finding the Achilles Heel of the Web of Data: Using Network Analysis for Link-Recommendation

Guéret¹,

Groth²,

Harmelen³

et al. 2010

Lecture Notes in Computer Science

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Abstract. The Web of Data is increasingly becoming an important infrastructure for such diverse sectors as entertainment, government, ecommerce and science. As a result, the robustness of this Web of Data is now crucial. Prior studies show that the Web of Data is strongly dependent on a small number of central hubs, making it highly vulnerable to single points of failure. In this paper, we present concepts and algorithms to analyse and repair the brittleness of the Web of Data. We apply these on a substantial subset of it, the 2010 Billion Triple Challenge dataset. We first distinguish the physical structure of the Web of Data from its semantic structure. For both of these structures, we then calculate their robustness, taking betweenness centrality as a robustnessmeasure. To the best of our knowledge, this is the first time that such robustness-indicators have been calculated for the Web of Data. Finally, we determine which links should be added to the Web of Data in order to improve its robustness most effectively. We are able to determine such links by interpreting the question as a very large optimisation problem and deploying an evolutionary algorithm to solve this problem. We believe that with this work, we offer an effective method to analyse and improve the most important structure that the Semantic Web community has constructed to date.

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“…Relatively li le is known about the structural properties of the Semantic Web. Early work in this area has observed the presence of power-law distributions and other network-based features, such as clustering coe cient and path lengths, over individual datasets of (up to) millions of triples [4,9,7]. It is not yet known whether the structural properties of the LOD Cloud are the same as the structural properties of individual datasets.…”

Section: Use Cases For Data Sciencementioning

confidence: 99%

LOD-a-lot

Beek

Fernández

Verborgh

2017

Proceedings of the 13th International Conference on Semantic Systems

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Many data scientists make use of Linked Open Data (LOD) as a huge interconnected knowledge base represented in RDF. However, the distributed nature of the information and the lack of a scalable approach to manage and consume such Big Semantic Data makes it di cult and expensive to conduct large-scale studies. As a consequence, most scientists restrict their analyses to one or two datasets (o en DBpedia) that contain at most hundreds of millions of triples. LOD-a-lot is a dataset that integrates a large portion (over 28 billion triples) of the LOD Cloud into a single ready-to-consume le that can be easily downloaded, shared and queried with a small memory footprint. is paper shows there exists a wide collection of Data Science use cases that can be performed over such a LOD-a-lot le. For these use cases LOD-a-lot signi cantly reduces the cost and complexity of conducting Data Science.

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Object Link Structure in the Semantic Web

Cited by 25 publications

References 21 publications

An empirical survey of Linked Data conformance

An empirical survey of Linked Data conformance

Finding the Achilles Heel of the Web of Data: Using Network Analysis for Link-Recommendation

LOD-a-lot

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