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A Document Database Query Language

  • Nieves R. Brisaboa
  • Miguel R. Penabad
  • Ángeles S. Places
  • Francisco J. Rodríguez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2405)

Abstract

This work presents a natural language based technique to build user interfaces to query document databases through the web. We call such technique Bounded Natural Language (BNL). Interfaces based on BNL are useful to query document databases containing only structured data, containing only text or containing both of them. That is, the underlying formalism of BNL can integrate restrictions over structured and non-structured data (as text).

Interfaces using BNL can be programmed ad hoc for any document database but in this paper we present a system with an ontology based architecture in which the user interface is automatically generated by a software module (User Interface Generator) capable of reading and following the ontology. This ontology is a conceptualization of the database model, which uses a label in natural language for any concept in the ontology. Each label represents the usual name for a concept in the real world.

The ontology includes general concepts useful when the user is interested in documents in any corpus in the database, and specific concepts useful when the user is interested in a specific corpus. That is, databases can store one or more corpus of documents and queries can be issued either over the whole database or over a specific corpus.

The ontology guides the execution of the User Interface Generator and other software modules in such a way that any change in the database does not imply making changes in the program code, because the whole system runs following the ontology. That is, if a modification in the database schema occurs, only the ontology must be changed and the User Interface Generator will produce a new and different user interface adapted to the new database.

Keywords

Database Schema Text Retrieval Query User Interface Query System Natural Language Sentence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Nieves R. Brisaboa
    • 1
  • Miguel R. Penabad
    • 1
  • Ángeles S. Places
    • 1
  • Francisco J. Rodríguez
    • 1
  1. 1.Dep. de ComputaciónUniv. de A CoruñaA CoruñaEspaña

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