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IEEE International Conference on Semantic Computing (ICSC 2011).
A Multidimensional Semantic Space for Data Model Independent Queries over RDF Data
André Freitas, João Gabriel Oliveira, Edward Curry Seán 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.