by Andre Freitas, Joao Gabriel Oliveira, Edward Curry, Se´n O'Riain
Abstract:
The vision of creating a Linked Data Web brings together the challenge of allowing queries across highly heterogeneous and distributed datasets. In order to query Linked Data on the Web today, end-users need to be aware of which datasets potentially contain the data and also which data model describes these datasets. The process of allowing users to expressively query relationships in RDF while abstracting them from the underlying data model represents a fundamental problem for Web-scale Linked Data consumption. This article introduces a multidimensional semantic space model which enables data model independent natural language queries over RDF data. The center of the approach relies on the use of a distributional semantic model to address the level of semantic interpretation demanded to build the data model independent approach. The final multidimensional semantic space proved to be flexible and precise under real-world query conditions achieving mean reciprocal rank = 0.516, avg. precision = 0.482 and avg. recall = 0.491
Reference:
Andre Freitas, Joao Gabriel Oliveira, Edward Curry, Se´n O'Riain, "A Multidimensional Semantic Space for Data Model Independent Queries over RDF Data", In 2011 IEEE Fifth International Conference on Semantic Computing, IEEE, pp. 344-351, 2011. [slides]
Bibtex Entry:
@inproceedings{Freitas2011d,
abstract = {The vision of creating a Linked Data Web brings together the challenge of allowing queries across highly heterogeneous and distributed datasets. In order to query Linked Data on the Web today, end-users need to be aware of which datasets potentially contain the data and also which data model describes these datasets. The process of allowing users to expressively query relationships in RDF while abstracting them from the underlying data model represents a fundamental problem for Web-scale Linked Data consumption. This article introduces a multidimensional semantic space model which enables data model independent natural language queries over RDF data. The center of the approach relies on the use of a distributional semantic model to address the level of semantic interpretation demanded to build the data model independent approach. The final multidimensional semantic space proved to be flexible and precise under real-world query conditions achieving mean reciprocal rank = 0.516, avg. precision = 0.482 and avg. recall = 0.491},
annote = {<a href="http://www.slideshare.net/andrenfreitas/icsc-2011-freitasetal3">[slides]</a>},
author = {Freitas, Andre and Oliveira, Joao Gabriel and Curry, Edward and O'Riain, Se´n},
booktitle = {2011 IEEE Fifth International Conference on Semantic Computing},
doi = {10.1109/ICSC.2011.89},
file = {:Users/ed/Library/Application Support/Mendeley Desktop/Downloaded/Freitas et al. - 2011 - A Multidimensional Semantic Space for Data Model Independent Queries over RDF Data.pdf:pdf},
isbn = {978-1-4577-1648-5},
keywords = {LEIdataspace,Treo},
mendeley-tags = {LEIdataspace,Treo},
month = {sep},
pages = {344--351},
publisher = {IEEE},
title = {{A Multidimensional Semantic Space for Data Model Independent Queries over RDF Data}},
url = {http://www.edwardcurry.org/publications/Freitas_ICSC_2011.pdf},
year = {2011}
}