Literatura científica selecionada sobre o tema "Requêtes mots clés"
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Artigos de revistas sobre o assunto "Requêtes mots clés"
Comparot, Catherine, Ollivier Haemmerlé e Nathalie Hernandez. "Production de requêtes SPARQL à partir de mots-clés et de patrons de requêtes". Techniques et sciences informatiques 32, n.º 7-8 (30 de outubro de 2013): 841–61. http://dx.doi.org/10.3166/tsi.32.841-861.
Texto completo da fonteAjiferuke, Isola, e Jamie Leigh Goodfellow. "Evaluation of the Effectiveness of Tag as an Access Point in a Public Library OPAC". Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l'ACSI, 28 de outubro de 2013. http://dx.doi.org/10.29173/cais623.
Texto completo da fonteKipp, Margaret E. I. "Comparing Controlled Vocabularies and Tags: Research Methodologies and Research Goals". Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l'ACSI, 21 de outubro de 2013. http://dx.doi.org/10.29173/cais573.
Texto completo da fonteKipp, Margaret E. I., e Jihee Beak. "Examining Studies Comparing Tags and Controlled Vocabularies". Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l'ACSI, 31 de outubro de 2013. http://dx.doi.org/10.29173/cais689.
Texto completo da fonteFaye, David C., Gilles Nachouki e Patrick Valduriez. "SenPeer : un système pair-à-pair de médiation de données". Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées Volume 4, 2006 (20 de outubro de 2006). http://dx.doi.org/10.46298/arima.1847.
Texto completo da fonteSitepu, Egalety, Jubliana Sitompul e Nurilam Harianja. "ACTE DE LANGAGE DE REQUÊTE DES ÉTUDIANTS DU QUATRIÈME SEMESTRE SECTION FRANÇAISE UNIVERSITÉ DE MEDAN L’ANNEÉ UNIVERSITAIRE 2013/2014". HEXAGONE Jurnal Pendidikan, Linguistik, Budaya dan Sastra Perancis 3, n.º 1 (17 de novembro de 2014). http://dx.doi.org/10.24114/hxg.v3i1.1404.
Texto completo da fonteTeses / dissertações sobre o assunto "Requêtes mots clés"
Rihany, Mohamad. "Keyword Search and Summarization Approaches for RDF Dataset Exploration". Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG030.
Texto completo da fonteAn increasing number of datasets are published on the Web, expressed in the standard languages proposed by the W3C such as RDF, RDF (S), and OWL. These datasets represent an unprecedented amount of data available for users and applications. In order to identify and use the relevant datasets, users and applications need to explore them using queries written in SPARQL, a query language proposed by the W3C. But in order to write a SPARQL query, a user should not only be familiar with the query language but also have knowledge about the content of the RDF dataset in terms of the resources, classes or properties it contains. The goal of this thesis is to provide approaches to support the exploration of these RDF datasets. We have studied two alternative and complementary exploration techniques, keyword search and summarization of an RDF dataset. Keyword search returns RDF graphs in response to a query expressed as a set of keywords, where each resulting graph is the aggregation of elements extracted from the source dataset. These graphs represent possible answers to the keyword query, and they can be ranked according to their relevance. Keyword search in RDF datasets raises the following issues: (i) identifying for each keyword in the query the matching elements in the considered dataset, taking into account the differences of terminology between the keywords and the terms used in the RDF dataset, (ii) combining the matching elements to build the result by defining aggregation algorithms that find the best way of linking matching elements, and finally (iii), finding appropriate metrics to rank the results, as several matching elements may exist for each keyword and consequently several graphs may be returned. In our work, we propose a keyword search approach that addresses these issues. Providing a summarized view of an RDF dataset can help a user in identifying if this dataset is relevant to his needs, and in highlighting its most relevant elements. This could be useful for the exploration of a given dataset. In our work, we propose a novel summarization approach based on the underlying themes of a dataset. Our theme-based summarization approach consists of extracting the existing themes in a data source, and building the summarized view so as to ensure that all these discovered themes are represented. This raises the following questions: (i) how to identify the underlying themes in an RDF dataset? (ii) what are the suitable criteria to identify the relevant elements in the themes extracted from the RDF graph? (iii) how to aggregate and connect the relevant elements to create a theme summary? and finally, (iv) how to create the summary for the whole RDF graph from the generated theme summaries? In our work, we propose a theme-based summarization approach for RDF datasets which answers these questions and provides a summarized representation ensuring that each theme is represented proportionally to its importance in the initial dataset