Extracting fuzzy summaries from nosql graph databases

Abstract : Linguistic summaries have been studied for many years and allow to sum up large volumes of data in a very intuitive manner. They have been studied over several types of data. However, few works have been led on graph databases. Graph databases are becoming popular tools and have recently gained significant recognition with the emergence of the so-called NoSQL graph databases. These databases allow users to handle huge volumes of data (e.g., scientific data, social networks). There are several ways to consider graph summaries. In this paper, we detail the specificities of NoSQL graph databases and we discuss how to summarize them by introducing several types of linguistic summaries, namely structure summaries, data structure summaries and fuzzy summaries. We present extraction methods that have been tested over synthetic and real database experimentations.
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Communication dans un congrès
FQAS: Flexible Query Answering Systems, Oct 2015, Cracow, Poland. 11th International Conference on Flexible Query Answering Systems, Advances in Intelligent Systems and Computing (400), pp.189-200, 2016, Flexible Query Answering Systems 2015. 〈10.1007/978-3-319-26154-6_15〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01381078
Contributeur : Anne Laurent <>
Soumis le : vendredi 14 octobre 2016 - 00:04:16
Dernière modification le : jeudi 11 janvier 2018 - 06:14:31

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Arnaud Castelltort, Anne Laurent. Extracting fuzzy summaries from nosql graph databases. FQAS: Flexible Query Answering Systems, Oct 2015, Cracow, Poland. 11th International Conference on Flexible Query Answering Systems, Advances in Intelligent Systems and Computing (400), pp.189-200, 2016, Flexible Query Answering Systems 2015. 〈10.1007/978-3-319-26154-6_15〉. 〈lirmm-01381078〉

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