The availability and the proliferation of ontologies are crucial for the success of the Semantic Web. As consequence, a great number of researchers are working on method and techniques to build ontologies through automatic or semi-automatic processes, which perform knowledge acquisition from texts, dictionaries and structured and semi-structured information sources. On the other hand, reverse engineering, when applied to software engineering, uses a collection of theories, methodologies and techniques to support information abstraction and extraction from a piece of software. In this paper we present a semi-automatic reverse engineering approach to acquire OWL ontology corresponding to the content of relational database. Our approach is based on the idea that the semantics extracted by analyzing HTML forms will be used to restructure and enrich the relational schema. OWL ontology is constructed through a set of transformation rules from the enriched schema. The main reason for this construction is to make the relational database information that is available on the Web machine-processable and reduce the time consuming task of ontology creation.
Description
Acquiring owl ontologies from data-intensive web sites
%0 Conference Paper
%1 1145593
%A Benslimane, Sidi Mohamed
%A Benslimane, Djamal
%A Malki, Mimoun
%A Amghar, Youssef
%A Saliah-Hassane, Hamadou
%B ICWE '06: Proceedings of the 6th international conference on Web engineering
%C New York, NY, USA
%D 2006
%I ACM
%K ontology ontologylearning
%P 361--368
%R http://doi.acm.org/10.1145/1145581.1145593
%T Acquiring owl ontologies from data-intensive web sites
%U http://portal.acm.org/citation.cfm?id=1145581.1145593&coll=ACM&dl=ACM&CFID=69871947&CFTOKEN=53159907
%X The availability and the proliferation of ontologies are crucial for the success of the Semantic Web. As consequence, a great number of researchers are working on method and techniques to build ontologies through automatic or semi-automatic processes, which perform knowledge acquisition from texts, dictionaries and structured and semi-structured information sources. On the other hand, reverse engineering, when applied to software engineering, uses a collection of theories, methodologies and techniques to support information abstraction and extraction from a piece of software. In this paper we present a semi-automatic reverse engineering approach to acquire OWL ontology corresponding to the content of relational database. Our approach is based on the idea that the semantics extracted by analyzing HTML forms will be used to restructure and enrich the relational schema. OWL ontology is constructed through a set of transformation rules from the enriched schema. The main reason for this construction is to make the relational database information that is available on the Web machine-processable and reduce the time consuming task of ontology creation.
%@ 1-59593-352-2
@inproceedings{1145593,
abstract = {The availability and the proliferation of ontologies are crucial for the success of the Semantic Web. As consequence, a great number of researchers are working on method and techniques to build ontologies through automatic or semi-automatic processes, which perform knowledge acquisition from texts, dictionaries and structured and semi-structured information sources. On the other hand, reverse engineering, when applied to software engineering, uses a collection of theories, methodologies and techniques to support information abstraction and extraction from a piece of software. In this paper we present a semi-automatic reverse engineering approach to acquire OWL ontology corresponding to the content of relational database. Our approach is based on the idea that the semantics extracted by analyzing HTML forms will be used to restructure and enrich the relational schema. OWL ontology is constructed through a set of transformation rules from the enriched schema. The main reason for this construction is to make the relational database information that is available on the Web machine-processable and reduce the time consuming task of ontology creation.},
added-at = {2008-05-26T09:54:54.000+0200},
address = {New York, NY, USA},
author = {Benslimane, Sidi Mohamed and Benslimane, Djamal and Malki, Mimoun and Amghar, Youssef and Saliah-Hassane, Hamadou},
biburl = {https://www.bibsonomy.org/bibtex/2492dc473287056ec9a27ea9ce8c14617/enterldestodes},
booktitle = {ICWE '06: Proceedings of the 6th international conference on Web engineering},
description = {Acquiring owl ontologies from data-intensive web sites},
doi = {http://doi.acm.org/10.1145/1145581.1145593},
interhash = {773fb67b682e0bcde4f1f09434f18acc},
intrahash = {492dc473287056ec9a27ea9ce8c14617},
isbn = {1-59593-352-2},
keywords = {ontology ontologylearning},
location = {Palo Alto, California, USA},
pages = {361--368},
publisher = {ACM},
timestamp = {2008-05-26T09:54:55.000+0200},
title = {Acquiring owl ontologies from data-intensive web sites},
url = {http://portal.acm.org/citation.cfm?id=1145581.1145593&coll=ACM&dl=ACM&CFID=69871947&CFTOKEN=53159907},
year = 2006
}