Advanced Retrieval From Heterogeneous Fact Databases: Integration of Data Retrieval, Conversion, Aggregation and Deductive Techniques.
Kalervo Järvelin, Timo Niemi:
Advanced Retrieval From Heterogeneous Fact Databases: Integration of Data Retrieval, Conversion, Aggregation and Deductive Techniques.
SIGIR 1991: 173-182@inproceedings{DBLP:conf/sigir/JarvelinN91,
author = {Kalervo J{\"a}rvelin and
Timo Niemi},
editor = {Abraham Bookstein and
Yves Chiaramella and
Gerard Salton and
Vijay V. Raghavan},
title = {Advanced Retrieval From Heterogeneous Fact Databases: Integration
of Data Retrieval, Conversion, Aggregation and Deductive Techniques},
booktitle = {Proceedings of the 14th Annual International ACM SIGIR Conference
on Research and Development in Information Retrieval. Chicago,
Illinois, USA, October 13-16, 1991 (Special Issue of the SIGIR
Forum)},
publisher = {ACM},
year = {1991},
isbn = {0-89791-448-1},
pages = {173-182},
ee = {db/conf/sigir/JarvelinN91.html},
crossref = {DBLP:conf/sigir/91},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
Abstract
Modern distributed fact databases are heterogeneous and autonomous. Their heterogeneity is due to many
reasons, including varying data models, data structures, attribute naming conventions, units of
measurement or naming of data values, composition of data as attributes, technical representation of
data, abstraction levels of data, etc. Database autonomity means that the database users have hardly
any means for reducing such heterogeneity. Present information retrieval (IR) systems either provide
no support for overcoming such heterogeneity or their support is insufficient and difficult to utilize.
In this paper we offer integrated and powerful data conversion, aggregation and deductive techniques
for advanced IR in such environments. These techniques allow the users to overcome data inconsistency
due to units of measurement or naming of data values, composition of data as attributes, abstraction
levels of data, and difficulties related to deductive use of hierarchically classified data.
In complex situations, all these inconsistencies appears together. Therefore we also show how these
techniques are integrated into a powerful query language which has been implemented in Prolog in a workstation environment.
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BibTeX
Printed Edition
Abraham Bookstein, Yves Chiaramella, Gerard Salton, Vijay V. Raghavan (Eds.):
Proceedings of the 14th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Chicago, Illinois, USA, October 13-16, 1991 (Special Issue of the SIGIR Forum).
ACM 1991, ISBN 0-89791-448-1
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