INDREX : in-database distributional relation extraction

Détails

ID Serval
serval:BIB_44917269F31E
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Titre
INDREX : in-database distributional relation extraction
Titre de la conférence
Proceedings of the sixteenth international workshop on Data warehousing and OLAP - DOLAP '13
Auteur⸱e⸱s
Kilias T., Löser A., Andritsos P.
Editeur
ACM Press
Adresse
San Francisco, California
ISBN
9781450324120
Statut éditorial
Publié
Date de publication
10/2013
Peer-reviewed
Oui
Série
Conference on Information and Knowledge Management
Pages
93-100
Langue
anglais
Résumé
Relation extraction transforms the textual representation of a relationship into the relational model of a data warehouse. Early systems, such as SystemT by IBM or the open source system GATE solve this task with handcrafted rule sets that the system executes document-by-document. Thereby the user must execute a highly interactive and iterative process of reading a document, of expressing rules, of testing these rules on the next document and of refining rules. Until now, these systems do neither leverage the full potential of built-in declarative query languages nor the indexing and query optimization techniques of a modern RDBMS that would enable a user interactive rule refinement across documents and on the entire corpus. We propose the INDREX system that enables a user for the first time to describe corpus-wide extraction tasks in a declarative language and permits the user to run interactive rule refinement queries. For enabling this powerful functionality we extend a standard PostgreSQL with a set of white-box user-defined functions that enable corpus-wide transformations from sentences into relationships. We store the text corpus and rules in the same RDBMS that already holds domain specific structured data. As a result, (1) the user can leverage this data to further adapt rules to the target domain, (2) the user does not need an additional system for rule extraction and (3) the INDREX system can leverage the full power of built-in indexing and query optimization techniques of the underlaying RDBMS. In a preliminary study we report on the feasibility of this disruptive approach and show multiple queries in INDREX on the Reuters Corpus, Volume 1.
Création de la notice
22/08/2017 13:21
Dernière modification de la notice
20/08/2019 13:49
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