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Completing RDF Data in Linked Open Data Cloud using Formal Concept Analysis
| Content Provider | Semantic Scholar |
|---|---|
| Author | Alam, Mehwish Buzmakov, Aleksey Codocedo, Víctor |
| Copyright Year | 2014 |
| Abstract | In the last years there has been a huge increase in the amount of information published as Linked Open Data (LOD). Its popularization and quick growth has led to challenging aspects regarding quality assessment and data exploration of the RDF triples that shape the LOD cloud. Particularly, we are interested in two important aspects of these challenges, namely how to deal with different data schemas and how to process heterogeneous resource descriptions. In this work we propose a novel technique to overcome these issues by the implementation of a knowledge discovery process based on Formal Concept Analysis which automatically detects incomplete information. We propose a structure for the organization of the RDF triples through a concept lattice of graph patterns, providing a powerful navigation mechanism while allowing for the discovery of implication rules that can be used to complete the LOD cloud. Such an organization also provides a way to help users in formulating specific SPARQL queries. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.semantic-web-journal.net/system/files/swj758.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
