Upgraded SemIndex Prototype Supporting Intelligent Database Keyword Queries through Disambiguation, Query as You Type, and Parallel Search Algorithms

Autor: Agma J. M. Traina, Joe Tekli, Caetano Traina, Carlos Arturo Raymundo Ibañez, Kokou Yetongnon, Christian Kallas, Richard Chbeir
Přispěvatelé: Lebanese American University (LAU), Laboratoire Informatique de l'Université de Pau et des Pays de l'Adour (LIUPPA), Université de Pau et des Pays de l'Adour (UPPA), Data Bases and Images Group (GBDI), Universidade de São Paulo (USP), Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508] (Le2i), Université de Technologie de Belfort-Montbeliard (UTBM)-Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Universidad Peruana de Ciencias Aplicadas (Lima) (UPC), National Council for Scientific Research (CNRS-L) - Lebanon, Lebanese American Unviersity (LAU), Research Support Foundation of the State of Sao Paulo (FAPESP), MIVisBD_2017
Rok vydání: 2018
Předmět:
Zdroj: ICCC
2018 IEEE INTERNATIONAL CONFERENCE ON COGNITIVE COMPUTING (ICCC)
2018 IEEE International Conference on Cognitive Computing, ICCC 2018, San Francisco, CA, USA, July 2-7, 2018
2018 IEEE International Conference on Cognitive Computing, ICCC 2018, San Francisco, CA, USA, July 2-7, 2018, Jul 2018, San Francisco, CA, United States. pp.33-40, ⟨10.1109/ICCC.2018.00012⟩
DOI: 10.1109/iccc.2018.00012
Popis: International audience; This paper describes an upgraded version of the SemIndex prototype system for semantic-aware search in textual SQL databases. Semantic-aware querying has emerged as a required extension of the standard containment keyword-based query to meet user needs in textual databases and IR applications. Here, we build on top of Semindex, a semantic-aware inverted index previously developed by our team, to allow semantic-aware search, result selection, and result ranking functionality. Various weighting functions and intelligent search algorithms have been developed for that purpose and will be presented here. A graphical interface was also added to help end-users write and execute queries. Preliminary experiments highlight SemIndex querying effectiveness and efficiency, considering different querying algorithms, different semantic coverages, and a varying number of query keywords.This paper describes an upgraded version of the SemIndex prototype system for semantic-aware search in textual SQL databases. Semantic-aware querying has emerged as a required extension of the standard containment keyword-based query to meet user needs in textual databases and IR applications. Here, we build on top of Semindex, a semantic-aware inverted index previously developed by our team, to allow semantic-aware search, result selection, and result ranking functionality. Various weighting functions and intelligent search algorithms have been developed for that purpose and will be presented here. A graphical interface was also added to help end-users write and execute queries. Preliminary experiments highlight SemIndex querying effectiveness and efficiency, considering different querying algorithms, different semantic coverages, and a varying number of query keywords.Semantic Queries; Inverted Index; Semantic Network; Textual Database; Semantic Search; Disambiguation ;XML
Databáze: OpenAIRE