The quality of the XML Web

Grijzenhout, Steven; Marx, Maarten

doi:10.1016/j.websem.2012.12.001

Cited by 33 publications

(13 citation statements)

References 27 publications

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“…Supporting such a rationale for the law actually triggers and fosters the development of the Web. Recent surveys on the quality of XML documents on the Web show that 85.4% (n = 180 K) are well-formed and 99.5% of all specified encodings is correct [54]. Even so, much of the Linked Open Data available on the Web is far from the five-star level [9], and about 40% of linked datasets have been published without a license [124], i.e., without appropriate legal coverage.…”

Section: Standardisation Trendsmentioning

confidence: 99%

Semantic Web for the Legal Domain: The next step

Casanovas

Palmirani

Peroni

et al. 2016

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Abstract. Ontology-driven systems with reasoning capabilities in the legal field are now better understood. Legal concepts are not discrete, but make up a dynamic continuum between common sense terms, specific technical use, and professional knowledge, in an evolving institutional reality. Thus, the tension between a plural understanding of regulations and a more general understanding of law is bringing into view a new landscape in which general legal frameworks -grounded in well-known legal theories stemming from 20th-century c. legal positivism or sociological jurisprudence -are made compatible with specific forms of rights management on the Web. In this sense, Semantic Web tools are not only being designed for information retrieval, classification, clustering, and knowledge management. They can also be understood as regulatory tools, i.e. as components of the contemporary legal architecture, to be used by multiple stakeholders -front-line practitioners, policymakers, legal drafters, companies, market agents, and citizens. That is the issue broadly addressed in this Special Issue on the Semantic Web for the Legal Domain, overviewing the work carried out over the last fifteen years, and seeking to foster new research in this field, beyond the state of the art.

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Section: Standardisation Trendsmentioning

confidence: 99%

Semantic Web for the Legal Domain: The next step

Casanovas

Palmirani

Peroni

et al. 2016

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“…Moreover, the disjunctive multiplicity schema can express the DTD from XMark [35], a well-known benchmark for XML data management. The disjunctive multiplicity schema also captures many of the DTDs from the real-world XML web collection proposed in [26].…”

Section: Extending Twig Learningmentioning

confidence: 99%

Learning queries for relational, semi-structured, and graph databases

Ciucanu

2013

Proceedings of the 2013 SIGMOD/PODS Ph.D. Symposium

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“…The presence of a schema for XML documents has many advantages, such as for query processing and optimization, development of database applications, data integration and exchange [15,42,34,18]. However, many XML documents in practice are not accompanied by a (valid) schema [3,37,36,6,41,25], making schema inference an attractive research problem [2,5,7,17,22,43,13,30,32]. Studying schema inference also has several practical motivations.…”

Section: Introductionmentioning

confidence: 99%

“…Studying schema inference also has several practical motivations. Schema inference techniques may be extended to schema repairing techniques [25]. Besides, schema inference is also useful in situations where a schema is already available, such as in schema cleaning and dealing with noise [7].…”

Section: Introductionmentioning

confidence: 99%

An effective algorithm for learning single occurrence regular expressions with interleaving

Chen

Zhang

et al. 2019

Proceedings of the 23rd International Database Applications &Amp; Engineering Symposium on - IDEAS '19

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The advantages offered by the presence of a schema are numerous. However, many XML documents in practice are not accompanied by a (valid) schema, making schema inference an attractive research problem. The fundamental task in XML schema learning is inferring restricted subclasses of regular expressions. Most previous work either lacks support for interleaving or only has limited support for interleaving. In this paper, we first propose a new subclass Single Occurrence Regular Expressions with Interleaving (SOIRE), which has unrestricted support for interleaving. Then, based on single occurrence automaton and maximum independent set, we propose an algorithm iSOIRE to infer SOIREs. Finally, we further conduct a series of experiments on real datasets to evaluate the effectiveness of our work, comparing with both ongoing learning algorithms in academia and industrial tools in real-world. The results reveal the practicability of SOIRE and the effectiveness of iSOIRE, showing the high preciseness and conciseness of our work.

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The quality of the XML Web

Cited by 33 publications

References 27 publications

Semantic Web for the Legal Domain: The next step

Semantic Web for the Legal Domain: The next step

Learning queries for relational, semi-structured, and graph databases

An effective algorithm for learning single occurrence regular expressions with interleaving

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