| Publications of year 2017 |
| Books and proceedings |
@proceedings{ICFCA2017,
title={Formal Concept Analysis: 14th International Conference, ICFCA 2017, Rennes, France, June 13-16, 2017, Proceedings},
editor={Bertet, Karell and Borchmann, Daniel and Cellier, Peggy and Ferré, Sébastien},
year={2017},
publisher={Springer},
series={LNAI10308},
keywords={formal concept analysis},
doi={10.1007/978-3-319-59271-8},
}
| Articles in journal or book chapters |
| Sparklis is a Semantic Web tool that helps users explore and query SPARQL endpoints by guiding them in the interactive building of questions and answers, from simple ones to complex ones. It combines the fine-grained guidance of faceted search, most of the expressivity of SPARQL, and the readability of (controlled) natural languages. No knowledge of the vocabulary and schema are required for users. Many SPARQL features are covered: multidimensional queries, union, negation, optional, filters, aggregations, ordering. Queries are verbalized in either English or French, so that no knowledge of SPARQL is ever necessary. All of this is implemented in a portable Web application, Sparklis, and has been evaluated on many endpoints and questions. No endpoint-specific configuration is necessary as the data schema is discovered on the fly by the tool. Online since April 2014, thousands of queries have been formed by hundreds of users over more than a hundred endpoints. |
@article{Fer2016swj,
author = {Sébastien Ferré},
title = {Sparklis: An Expressive Query Builder for {SPARQL} Endpoints with Guidance in Natural Language},
journal = {Semantic Web: Interoperability, Usability, Applicability},
publisher = {IOS Press},
year = {2017},
volume = {8},
number = {3},
pages = {405-418},
url = {http://www.semantic-web-journal.net/content/sparklis-expressive-query-builder-sparql-endpoints-guidance-natural-language-1},
doi = {10.3233/SW-150208},
abstract = { Sparklis is a Semantic Web tool that helps users explore and query SPARQL endpoints by guiding them in the interactive building of questions and answers, from simple ones to complex ones. It combines the fine-grained guidance of faceted search, most of the expressivity of SPARQL, and the readability of (controlled) natural languages. No knowledge of the vocabulary and schema are required for users. Many SPARQL features are covered: multidimensional queries, union, negation, optional, filters, aggregations, ordering. Queries are verbalized in either English or French, so that no knowledge of SPARQL is ever necessary. All of this is implemented in a portable Web application, Sparklis, and has been evaluated on many endpoints and questions. No endpoint-specific configuration is necessary as the data schema is discovered on the fly by the tool. Online since April 2014, thousands of queries have been formed by hundreds of users over more than a hundred endpoints.},
keywords = {semantic search, SPARQL endpoint, query builder, faceted search, natural language},
}
| Conference articles |
@inproceedings{ChevalierFerre2017iswc,
author = {Fabien Chevalier and Sébastien Ferré},
title = {Entering the Digital Customer Onboarding Era: How the Semantic Web Can Help},
booktitle = {Posters {\&} Demonstrations and Industry Tracks at Int. Semantic Web Conf.},
editor = {N. Nikitina and D. Song and A. Fokoue and P. Haase},
year = {2017},
series = {{CEUR} Workshop Proceedings},
volume = {1963},
publisher = {CEUR-WS.org},
pdf = {http://ceur-ws.org/Vol-1963/paper476.pdf},
keywords = {semantic web},
}
| Nous introduisons la notion de {\em concept de voisins} comme alternative à la notion de distance numérique dans le but d'identifier les objets les plus similaires à un objet requête, comme dans la méthode des plus proches voisins. Chaque concept de voisins est composé d'une intension qui décrit symboliquement ce que deux objets ont en commun et d'une extension qui englobe les objets qui se trouvent entre les deux. Nous définissons ces concepts de voisins pour des données complexes, les graphes de connaissances, où les n{\oe}uds jouent le rôle d'objets. Nous décrivons un algorithme {\em anytime} permettant d'affronter la complexité élevée de la tâche et nous présentons de premières expérimentations sur un graphe RDF de plus de 120.000 triplets. |
@inproceedings{Ferre2017ic,
title={Concepts de plus proches voisins dans des graphes de connaissances},
author={Sébastien Ferré},
booktitle={28es Journées francophones d'Ingénierie des Connaissances ({IC})},
pages={163--174},
year={2017},
pdf={https://hal.archives-ouvertes.fr/hal-01570277/file/paper\_cnn.pdf},
url={https://hal.archives-ouvertes.fr/hal-01570277},
keywords={semantic web, knowledge graph, nearest neighbours, concept},
abstract={Nous introduisons la notion de {\em concept de voisins} comme alternative à la notion de distance numérique dans le but d'identifier les objets les plus similaires à un objet requête, comme dans la méthode des plus proches voisins. Chaque concept de voisins est composé d'une intension qui décrit symboliquement ce que deux objets ont en commun et d'une extension qui englobe les objets qui se trouvent entre les deux. Nous définissons ces concepts de voisins pour des données complexes, les graphes de connaissances, où les n{\oe}uds jouent le rôle d'objets. Nous décrivons un algorithme {\em anytime} permettant d'affronter la complexité élevée de la tâche et nous présentons de premières expérimentations sur un graphe RDF de plus de 120.000 triplets.},
}
@inproceedings{Formulis17dexa,
author = {Pierre Maillot and Sébastien Ferré and Peggy Cellier and Mireille Ducassé and Franck Partouche},
title = {Nested Forms with Dynamic Suggestions for Quality {RDF} Authoring},
booktitle = {Int. Conf. Database and Expert Systems Applications ({DEXA})},
pages = {35--45},
year = {2017},
doi = {10.1007/978-3-319-64468-4_3},
url = {https://hal.inria.fr/hal-01731124},
keywords = {semantic web, RDF, knowledge acquisition, form, data quality},
}
| Miscellaneous |
@misc{icfcademo17,
author={Hedi-Th\'{e}o Sahraoui and Pierre Holat and Peggy Cellier and Thierry Charnois and S\'{e}bastien Ferr\'{e}},
title="Exploration of Textual Sequential Patterns",
booktitle="Suppl. Proc. ICFCA",
year="2017",
}
@Unpublished{Fer2017semantics,
author = {Sébastien Ferré},
title = {Sparklis: An Expressive Query Builder for SPARQL Endpoints with Guidance in Natural Language},
note = {Poster and demo at SEMANTiCS 2017, Amsterdam},
year = {2017},
}
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