-
Mouhamadou Ba.
Guided Composition of Tasks with Logical Information Systems - Application to Data Analysis Workflows in Bioinformatics.
In P. Cimiano,
O. Corcho,
V. Presutti,
L. Hollink,
and S. Rudolph, editors,
Extended Semantic Web Conf.,
LNCS 7882,
pages 661-665,
2013.
Springer.
@inproceedings{Ba2013,
author = {Mouhamadou Ba},
title = {Guided Composition of Tasks with Logical Information Systems - Application to Data Analysis Workflows in Bioinformatics},
booktitle = {Extended Semantic Web Conf.},
year = {2013},
pages = {661-665},
editor = {P. Cimiano and O. Corcho and V. Presutti and L. Hollink and S. Rudolph},
publisher = {Springer},
series = {LNCS 7882},
}
-
Mireille Ducassé.
Helping Facilitators Build on Experience When Preparing Meetings With Logical Information Systems.
In Bilyana Martinovski, editor,
Group Decision and Negotiation Conference,
pages 139-143,
2013.
Department of Computer and Systems Sciences, Stockholm University.
Note: Extended abstract.
Keyword(s): Artificial Intelligence Methods in GDN,
Logical information systems,
Concept Analysis Application,
Facilitator support,
Agenda building,
ThinkLets.
Abstract: |
This paper reports work in progress about using Logical Information Systems to help facilitators build on experience when preparing meetings. Features of meetings similar to the one under construction are automatically suggested without having to ask for suggestions. Suggestions take into account the whole information about all the meetings already recorded in the system as well as facilitation knowledge, such as thinkLets. Usual techniques and processes that facilitators like to use are naturally suggested. An unusual technique is suggested for example if the facilitator enters a keyword that is a feature of that technique. Although a lot remains to be done, the proposed approach already shows contributions that make believe that it is worth investigating further. The main one is that it builds on the facilitator very practice. Other important features are flexibility and adaptability. |
@InProceedings{ducasse2013,
Author={Mireille Ducassé},
Title={Helping Facilitators Build on Experience When Preparing Meetings With Logical Information Systems},
Pages={139-143},
Organization={ },
BookTitle={Group Decision and Negotiation Conference},
Year={2013},
Editor={Bilyana Martinovski},
Publisher={Department of Computer and Systems Sciences, Stockholm University},
Note={Extended abstract},
Keywords={Artificial Intelligence Methods in GDN, Logical information systems, Concept Analysis Application, Facilitator support, Agenda building, ThinkLets},
Url={ },
Abstract={This paper reports work in progress about using Logical Information Systems to help facilitators build on experience when preparing meetings. Features of meetings similar to the one under construction are automatically suggested without having to ask for suggestions. Suggestions take into account the whole information about all the meetings already recorded in the system as well as facilitation knowledge, such as thinkLets. Usual techniques and processes that facilitators like to use are naturally suggested. An unusual technique is suggested for example if the facilitator enters a keyword that is a feature of that technique. Although a lot remains to be done, the proposed approach already shows contributions that make believe that it is worth investigating further. The main one is that it builds on the facilitator very practice. Other important features are flexibility and adaptability. }
}
-
Sébastien Ferré.
Representation of Complex Expressions in RDF.
In P. Cimiano,
M. Fernández,
V. Lopez,
S. Schlobach,
and J. Völker, editors,
Extended Semantic Web Conf. (ESWC Satellite Events),
LNCS 7955,
pages 273-274,
2013.
Springer.
[PDF]
Keyword(s): semantic web,
RDF,
blank nodes,
expressions,
knowledge representation,
querying,
query-based faceted search,
mathematical search.
@inproceedings{Fer2013eswc,
author = {Sébastien Ferré},
title = {Representation of Complex Expressions in RDF},
booktitle = {Extended Semantic Web Conf. (ESWC Satellite Events)},
year = {2013},
pages = {273-274},
editor = {P. Cimiano and M. Fernández and V. Lopez and S. Schlobach and J. Völker},
publisher = {Springer},
series = {LNCS 7955},
keywords = {semantic web, RDF, blank nodes, expressions, knowledge representation, querying, query-based faceted search, mathematical search},
asbtract = {Complex expressions, as used in mathematics and logics, account for a large part of human knowledge. It is therefore desirable to allow for their representation and search in RDF. We propose an approach\footnote{A long version of this paper is available at { t http://hal.inria.fr/hal-00812197}.} that fulfills three objectives: (1) the accurate representation of expressions in standard RDF, so that expressive search is made possible, (2) the automated generation of human-readable labels for expressions, and (3) the compatibility with legacy data (e.g., OWL/RDF, SPIN).},
pdf = {http://hal.inria.fr/hal-00943516/PDF/main.pdf},
}
-
Sébastien Ferré.
SQUALL: A Controlled Natural Language as Expressive as SPARQL 1.1.
In E. Métais,
F. Meziane,
M. Saraee,
V. Sugumaran,
and S. Vadera, editors,
Int. Conf. Applications of Natural Language to Information System (NLDB),
LNCS 7934,
pages 114-125,
2013.
Springer.
[PDF]
Keyword(s): controlled natural language,
query language,
update language,
semantic web,
SPARQL,
expressivity.
Abstract: |
The Semantic Web is now made of billions of triples, which are available as Linked Open Data (LOD) or as RDF stores. The most common approach to access RDF datasets is through SPARQL, an expressive query language. However, SPARQL is difficult to learn for most users because it exhibits low-level notions of relational algebra such as union, filters, or grouping. We present SQUALL, a high-level language for querying and updating an RDF dataset. It has a strong compliance with RDF, covers all features of SPARQL 1.1, and has a controlled natural language syntax that completely abstracts from low-level notions. SQUALL is available as two web services: one for translating a SQUALL sentence to a SPARQL query or update, and another for directly querying a SPARQL endpoint such as DBpedia. |
@inproceedings{Fer2013nldb,
author = {Sébastien Ferré},
title = {SQUALL: A Controlled Natural Language as Expressive as {SPARQL} 1.1},
booktitle = {Int. Conf. Applications of Natural Language to Information System ({NLDB})},
year = {2013},
pages = {114-125},
editor = {E. Métais and F. Meziane and M. Saraee and V. Sugumaran and S. Vadera},
publisher = {Springer},
series = {LNCS 7934},
keywords = {controlled natural language, query language, update language, semantic web, SPARQL, expressivity},
abstract = {The Semantic Web is now made of billions of triples, which are available as Linked Open Data (LOD) or as RDF stores. The most common approach to access RDF datasets is through SPARQL, an expressive query language. However, SPARQL is difficult to learn for most users because it exhibits low-level notions of relational algebra such as union, filters, or grouping. We present SQUALL, a high-level language for querying and updating an RDF dataset. It has a strong compliance with RDF, covers all features of SPARQL 1.1, and has a controlled natural language syntax that completely abstracts from low-level notions. SQUALL is available as two web services: one for translating a SQUALL sentence to a SPARQL query or update, and another for directly querying a SPARQL endpoint such as DBpedia.},
pdf = {http://hal.inria.fr/hal-00943510/PDF/main.pdf},
}
-
Alice Hermann,
Mireille Ducassé,
Sébastien Ferré,
and Jean Lieber.
Une approche fondée sur le raisonnement à partir de cas pour la mise à jour interactive d'objets du Web sémantique.
In 21ème atelier Français de Raisonnement à Partir de Cas (RàPC),
Lille, France,
2013.
[WWW]
Keyword(s): mise à jour d'objets,
Web sémantique,
RDFS,
formulaire de saisie,
recherche de cas par relâchement.
@inproceedings{HerDucFerLie2013,
author = {Hermann, Alice and Ducass{\'e}, Mireille and Ferr{\'e}, S{\'e}bastien and Lieber, Jean},
title = {{Une approche fond{\'e}e sur le raisonnement {\`a} partir de cas pour la mise {\`a} jour interactive d'objets du Web s{\'e}mantique}},
booktitle = {{21{\`e}me atelier Fran{\c c}ais de Raisonnement {\`a} Partir de Cas (R{\`a}PC)}},
year = {2013},
keywords = {mise {\`a} jour d'objets; Web s{\'e}mantique; RDFS; formulaire de saisie; recherche de cas par rel{\^a}chement},
address = {Lille, France},
url = {http://hal.inria.fr/hal-00910294},
}
-
Solen Quiniou,
Peggy Cellier,
Thierry Charnois,
and Dominique Legallois.
Graph Mining under Linguistic Constraints to Explore Large Texts.
In Intelligent Text Processing and Computational Linguistics (CICLing'13),
2013.
@inproceedings{QuiniouCCL13,
author = {Solen Quiniou and Peggy Cellier and Thierry Charnois and Dominique Legallois},
title = {Graph Mining under Linguistic Constraints to Explore Large Texts},
booktitle = {Intelligent Text Processing and Computational Linguistics (CICLing'13)},
year = {2013}
}
-
Joris Guyonvarch,
Sébastien Ferré,
and Mireille Ducassé.
Scalable Query-based Faceted Search on top of SPARQL Endpoints for Guided and Expressive Semantic Search.
Research report PI-2009,
LIS - IRISA,
October 2013.
[WWW]
[PDF]
Keyword(s): Web of data,
semantic search,
querying,
faceted search,
SPARQL,
SEWELIS,
expressivity,
usability,
scalability.
Abstract: |
Because the Web of Documents is composed of structured pages that are not meaningful to machines, search in the Web of Documents is generally processed by keywords. However, because the Web of Data provides structured information, search in the Web of Data can be more precise. SPARQL is the standard query language for querying this structured information. SPARQL is expressive and its syntax is similar to SQL. However, casual user can not write SPARQL queries. Sewelis is a search system for the Web of Data offering to explore data progressively and more user-friendly than SPARQL. Sewelis guides the search with a query built incrementally because users only have to select query elements in order to complete the query. However, Sewelis does not scale to large datasets such as DBpedia, which is composed of about 2 billion triples. In this report, we introduce Scalewelis. Scalewelis is a search system for the Web of Data that is similar to Sewelis but scalable. Moreover, Scalewelis is independent to data because it connects to SPARQL endpoints. We took part in a challenge on DBpedia with Scalewelis. We were able to answer to 70 questions out of 99 with acceptable response times. |
@techreport{GuyFerDuc2013pi,
hal_id = {hal-00868460},
url = {http://hal.inria.fr/hal-00868460},
title = {{Scalable Query-based Faceted Search on top of SPARQL Endpoints for Guided and Expressive Semantic Search}},
author = {Guyonvarch, Joris and Ferré, Sébastien and Ducassé, Mireille},
abstract = {{Because the Web of Documents is composed of structured pages that are not meaningful to machines, search in the Web of Documents is generally processed by keywords. However, because the Web of Data provides structured information, search in the Web of Data can be more precise. SPARQL is the standard query language for querying this structured information. SPARQL is expressive and its syntax is similar to SQL. However, casual user can not write SPARQL queries. Sewelis is a search system for the Web of Data offering to explore data progressively and more user-friendly than SPARQL. Sewelis guides the search with a query built incrementally because users only have to select query elements in order to complete the query. However, Sewelis does not scale to large datasets such as DBpedia, which is composed of about 2 billion triples. In this report, we introduce Scalewelis. Scalewelis is a search system for the Web of Data that is similar to Sewelis but scalable. Moreover, Scalewelis is independent to data because it connects to SPARQL endpoints. We took part in a challenge on DBpedia with Scalewelis. We were able to answer to 70 questions out of 99 with acceptable response times.}},
keywords = {Web of data; semantic search; querying; faceted search; SPARQL; SEWELIS; expressivity; usability; scalability},
language = {Anglais},
institution = {LIS - IRISA},
pages = {28},
type = {Research report},
number = {PI-2009},
year = {2013},
month = Oct,
pdf = {http://hal.inria.fr/hal-00868460/PDF/main.pdf},
}
-
Nicolas Béchet,
Peggy Cellier,
Thierry Charnois,
and Bruno Crémilleux.
Extraction de motifs séquentiels sous contraintes multiples,
2013.
Keyword(s): data mining,
sequential patterns,
linguistic pattern,
natural language processing.
@misc{BCCC13_1,
author = {Nicolas Béchet and Peggy Cellier and Thierry Charnois and Bruno Crémilleux},
title = {Extraction de motifs séquentiels sous contraintes multiples},
booktitle = {Extraction et gestion des connaissances (EGC'2013) (Session poster)},
year = {2013},
keywords = {data mining, sequential patterns, linguistic pattern, natural language processing},
editor = {Alexander F. Gelbukh}
}
-
Nicolas Béchet,
Peggy Cellier,
Thierry Charnois,
and Bruno Crémilleux.
SDMC : un outil en ligne d extraction de motifs se quentiels pour la fouille de textes,
2013.
Keyword(s): data mining,
sequential patterns,
linguistic pattern,
natural language processing.
@misc{BCCC13_2,
author = {Nicolas Béchet and Peggy Cellier and Thierry Charnois and Bruno Crémilleux},
title = {SDMC : un outil en ligne d extraction de motifs se quentiels pour la fouille de textes},
booktitle = {Extraction et gestion des connaissances (EGC'2013) (Session démo)},
year = {2013},
keywords = {data mining, sequential patterns, linguistic pattern, natural language processing},
editor = {Alexander F. Gelbukh}
}
-
Sébastien Ferré.
squall2sparql: a Translator from Controlled English to Full SPARQL 1.1.
Work. Multilingual Question Answering over Linked Data (QALD-3),
2013.
Note: See Online Working Notes at www.clef2013.org.
[PDF]
Keyword(s): squall,
controlled natural language,
question answering,
SPARQL.
Abstract: |
This paper reports on the participation of the system {\sc squall2sparql} in the QALD-3 question answering challenge for DBpedia. {\sc squall2sparql} is a translator from SQUALL, a controlled natural language for English, to SPARQL 1.1, a standard expressive query and update language for linked open data. It covers nearly all features of SPARQL 1.1, and is directly applicable to any SPARQL endpoint. |
@misc{QALD3:SQUALL,
author = {Sébastien Ferré},
title = {squall2sparql: a Translator from Controlled English to Full SPARQL 1.1},
howpublished = {Work. Multilingual Question Answering over Linked Data (QALD-3)},
editor = {C. Unger {et~al.}},
year = {2013},
note = {See Online Working Notes at { t www.clef2013.org}},
keywords = {squall, controlled natural language, question answering, SPARQL},
abstract = {This paper reports on the participation of the system {\sc squall2sparql} in the QALD-3 question answering challenge for DBpedia. {\sc squall2sparql} is a translator from SQUALL, a controlled natural language for English, to SPARQL 1.1, a standard expressive query and update language for linked open data. It covers nearly all features of SPARQL 1.1, and is directly applicable to any SPARQL endpoint.},
pdf = {http://hal.inria.fr/hal-00943522/PDF/main.pdf},
}
-
Joris Guyonvarc'h and Sébastien Ferré.
Scalewelis: a Scalable Query-based Faceted Search System on Top of SPARQL Endpoints.
Work. Multilingual Question Answering over Linked Data (QALD-3),
2013.
Note: See Online Working Notes at www.clef2013.org.
[PDF]
Keyword(s): faceted search,
question answering,
SEWELIS,
SPARQL.
Abstract: |
This paper overviews the participation of Scalewelis in the QALD-3 open challenge. Scalewelis is a Faceted Search system. Faceted Search systems refine the result set at each navigation step. In Scalewelis, refinements are syntactic operations that modify the user query. Scalewelis uses the Semantic Web standards (URI, RDF, SPARQL) and connects to SPARQL endpoints. |
@misc{QALD3:SCALEWELIS,
author = {Joris Guyonvarc'h and Sébastien Ferré},
title = {Scalewelis: a Scalable Query-based Faceted Search System on Top of SPARQL Endpoints},
howpublished = {Work. Multilingual Question Answering over Linked Data (QALD-3)},
editor = {C. Unger {et~al.}},
year = {2013},
note = {See Online Working Notes at { t www.clef2013.org}},
keywords = {faceted search, question answering, SEWELIS, SPARQL},
abstract = {This paper overviews the participation of Scalewelis in the QALD-3 open challenge. Scalewelis is a Faceted Search system. Faceted Search systems refine the result set at each navigation step. In Scalewelis, refinements are syntactic operations that modify the user query. Scalewelis uses the Semantic Web standards (URI, RDF, SPARQL) and connects to SPARQL endpoints.},
pdf = {http://hal.inria.fr/hal-00943528/PDF/main.pdf},
}