Contribution to the Classification of Web of Data based on Formal Concept Analysis
| Autor: | Reynaud, Justine, Toussaint, Yannick, Napoli, Amedeo |
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| Přispěvatelé: | Knowledge representation, reasonning (ORPAILLEUR), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: | |
| Zdroj: | What can FCA do for Artificial Intelligence (FCA4AI) (ECAI 2016) What can FCA do for Artificial Intelligence (FCA4AI) (ECAI 2016), Aug 2016, La Haye, Netherlands |
| Popis: | International audience; During the last decade, the web has taken a huge importance in everyday life, and has become what is commonly called a web of data. The available resources can be used by human agents but also by software agents, as it is the case for very large ontologies such as YAGO or resources such as DBpedia. These particular datasets can be linked together for constituting the Linked Open Data (LOD) cloud, where basic data are expressed as (subject, predicate, object) triples. One issue of main interest is knowledge discovery within LOD, which can help information retrieval and knowledge engineering. Formal concept analysis (FCA), which is a mathematical theory allowing classification and data analysis, was already used to classify LOD elements. In this research work, we are interested in analyzing the different approaches (extensions) based on FCA for knowledge discovery in the web of data. One objective is to study the efficiency and the applicability of the existing approaches and to propose some improvements. |
| Databáze: | OpenAIRE |
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