Combining Artificial Intelligence and Databases for Data Integration
A. Levy. Special issue of LNAI: Artificial Intelligence Today; RecentTrends and Developments, (1999)
Abstract
Data integration is a problem at the intersection of the fields of Artificial Intelligence and Database Systems. The goal of a data integration system is to provide a uniform interface to a multitude of data sources, whether they are within one enterprise or on the World-Wide Web. The key challenges in data integration arise because the data sources being integrated have been designed independently for autonomous applications, and their contents are related in subtle ways. As a result, a data integration system requires rich formalisms for describing contents of data sources and relating between contents of different sources. This paper discusses works aimed at applying techniques from...
%0 Journal Article
%1 Levy:1999
%A Levy, Alon Y.
%D 1999
%J Special issue of LNAI: Artificial Intelligence Today; RecentTrends and Developments
%K AI
%T Combining Artificial Intelligence and Databases for Data Integration
%U http://citeseer.nj.nec.com/211802.html
%X Data integration is a problem at the intersection of the fields of Artificial Intelligence and Database Systems. The goal of a data integration system is to provide a uniform interface to a multitude of data sources, whether they are within one enterprise or on the World-Wide Web. The key challenges in data integration arise because the data sources being integrated have been designed independently for autonomous applications, and their contents are related in subtle ways. As a result, a data integration system requires rich formalisms for describing contents of data sources and relating between contents of different sources. This paper discusses works aimed at applying techniques from...
@article{Levy:1999,
abstract = {Data integration is a problem at the intersection of the fields of Artificial Intelligence and Database Systems. The goal of a data integration system is to provide a uniform interface to a multitude of data sources, whether they are within one enterprise or on the World-Wide Web. The key challenges in data integration arise because the data sources being integrated have been designed independently for autonomous applications, and their contents are related in subtle ways. As a result, a data integration system requires rich formalisms for describing contents of data sources and relating between contents of different sources. This paper discusses works aimed at applying techniques from...},
added-at = {2007-12-14T02:42:20.000+0100},
author = {Levy, Alon Y.},
biburl = {https://www.bibsonomy.org/bibtex/2c7138db3bc526a9be848c543a15162d0/diego_ma},
interhash = {74fbec8ee3a5ecf8be8ada90ebbdf18e},
intrahash = {c7138db3bc526a9be848c543a15162d0},
journal = {Special issue of LNAI: Artificial Intelligence Today; RecentTrends and Developments},
keywords = {AI},
timestamp = {2007-12-14T03:25:30.000+0100},
title = {Combining Artificial Intelligence and Databases for Data Integration},
url = {http://citeseer.nj.nec.com/211802.html},
year = 1999
}