| Authors: |
Anand Ranganathan
and Zhen Liu
|
| URL: |
http://portal.acm.org/citation.cfm?id=1183747 |
| Description: |
Information retrieval from relational databases using semantic queries |
| Tags: |
imported
ir
query
semantic
|
| Abstract: |
Relational databases are widely used today as a mechanism for providing access to structured data. They, however, are not suitable for typical information finding tasks of end users. There is often a semantic gap between the queries users want to express and the queries that can be answered by the database. In this paper, we propose a system that bridges this semantic gap using domain knowledge contained in ontologies. Our system extends relational databases with the ability to answer semantic queries that are represented in SPARQL, an emerging Semantic Web query language. Users express their queries in SPARQL, based on a semantic model of the data, and they get back semantically relevant results. We define different categories of results that are semantically relevant to the users' query and show how our system retrieves these results. We evaluate the performance of our system on sample relational databases, using a combination of standard and custom ontologies. |
@inproceedings{1183747,
title = {Information retrieval from relational databases using semantic queries},
address = {New York, NY, USA},
author = {Anand Ranganathan and Zhen Liu},
booktitle = {CIKM '06: Proceedings of the 15th ACM international conference on Information and knowledge management},
pages = {820--821},
publisher = {ACM},
url = {http://portal.acm.org/citation.cfm?id=1183747},
year = {2006},
description = {Information retrieval from relational databases using semantic queries},
abstract = {Relational databases are widely used today as a mechanism for providing access to structured data. They, however, are not suitable for typical information finding tasks of end users. There is often a semantic gap between the queries users want to express and the queries that can be answered by the database. In this paper, we propose a system that bridges this semantic gap using domain knowledge contained in ontologies. Our system extends relational databases with the ability to answer semantic queries that are represented in SPARQL, an emerging Semantic Web query language. Users express their queries in SPARQL, based on a semantic model of the data, and they get back semantically relevant results. We define different categories of results that are semantically relevant to the users' query and show how our system retrieves these results. We evaluate the performance of our system on sample relational databases, using a combination of standard and custom ontologies.},
doi = {http://doi.acm.org/10.1145/1183614.1183747}, isbn = {1-59593-433-2}, location = {Arlington, Virginia, USA},
keywords = {imported ir query semantic }
}
::