Conceptual data retrieval from FDB Databases
Keywords:databases, conceptual search, multilingual thesaurus, information retrieval, FDB
FDB is a set theoretical model which allows the definition of multilingual databases and thesauri through a universal schema. One or more multilingual thesauri can be defined in the FDB model while the linking of each frame object (data record in terms of a traditional database) with the underlying thesauri can be implemented automatically. FDB offers administration utilities at both data and interface level, the definition of variable length objects, authority control etc. The purpose of this paper is to present the implementation of conceptual searching in any FDB database by using the information provided by one or more multilingual thesauri that have been already defined in the FDB model. Many different parameters can define the conceptual searching process in an FDB database. In this paper we firstly present briefly the FDB model, and proceed to present a) the search algorithms that exploit the information provided by the multilingual thesauri and implement conceptual searching in any FDB database, b) all the parameters that the user can define in order to determine the different search criteria.
E. Petraki, C. Kapetis, E.J. Yannakoudakis, (2013). Conceptual database retrieval through multilingual thesauri, Computer Science and Information Technology 1(1): 19-32,
E. J. Yannakoudakis, P. K. Andrikopoulos, (2007). A set-theoretic data model for evolving database environments, In Proceedings of the International Conference on Information & Knowledge Engineering, IKE 2007, Las Vegas, Nevada, USA.
Yannakoudakis E.J., Tsionos C.X. and Kapetis C.A, (1999). A new framework for dynamically evolving database environments, Journal of Documentation, Vol. 55, No. 2, pp. 144-158.
E. J. Yannakoudakis, (1987). An efficient file structure for specialised dictionaries and other 'lumpy' data, International Journal of Information Processing & Management, Vol. 23, No. 6, pp. 563-571.
E. Petraki, C. Kapetis, E.J. Yannakoudakis, (2014). Automated thesaurus population and management, In 6th International Conference on Qualitative and Quantitative Methods in Libraries, Istanbul
Yu Xu, Yannis Papakonstantinou, (2005). Efficient Keyword Search for Smallest LCAs in XML Databases, DOI: 10.1145/1066157.1066217 Conference: Proceedings of the ACM SIGMOD International Conference on Management of Data, Baltimore, Maryland, USA, June 14-16, 2005
Shashi K. Gadia, (1988). A Homogeneous Relational Model and Query Languages for Temporal Databases, ACM Transactions on Database Systems, Vol. 13, No. 4, December 1988, Pages 418-448.
Yannakoudakis E. J., and Nitsiou M. (2006), A new conceptual universal database language (CUDL), In 2nd International Conference From Scientific Computing to Computational Engineering, Athens, Greece.
Ángel F. Zazo, Carlos G. Figuerola, José L. Alonso Berrocal, Emilio Rodrı́guez, (2005), Reformulation of queries using similarity thesauri, Information Processing & Management, Volume 41, Issue 5, September 2005, Pages 1163–1173
R Baeza-Yates, B Ribeiro-Neto, (1999). Modern Information Retrieval, Book, Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA, ISBN:020139829X, ACM Press
Copyright (c) 2023 Qualitative and Quantitative Methods in Libraries
This work is licensed under a Creative Commons Attribution 4.0 International License.