Paper Info
Title
RDF Graph Summarization Based on Approximate Patterns.
Abstract
The Linked Open Data (LOD) cloud brings together information described in RDF and stored on the web in (possibly distributed) RDF Knowledge Bases (KBs). The data in these KBs are not necessarily described by a known schema and many times it is extremely time consuming to query all the interlinked KBs in order to acquire the necessary information. But even when the KB schema is known, we need actually to know which parts of the schema are used. We solve this problem by summarizing large RDF KBs using top-K approximate RDF graph patterns, which we transform to an RDF schema that describes the contents of the KB. This schema describes accurately the KB, even more accurately than an existing schema because it describes the actually used schema, which corresponds to the existing data. We add information on the number of various instances of the patterns, thus allowing the query to estimate the expected results. That way we can then query the RDF graph summary to identify whether the necessary information is present and if it is present in significant numbers whether to be included in a federated query result.
Year
DOI
Venue
2015
10.1007/978-3-319-43862-7_4
Communications in Computer and Information Science
Keywords
Field
DocType
RDF graph summary,Approximate patterns,RDF query,Linked Open Data,Federated query
Blank node,RDF query language,Information retrieval,Computer science,Cwm,Linked data,SPARQL,RDF/XML,RDF Schema,RDF
Conference
Volume
ISSN
Citations 
622
1865-0929
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Mussab Zneika100.34
Claudio Lucchese2110473.76
Dan Vodislav320.75
Dimitris Kotzinos492.21