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Mining conceptual graphs for knowledge acquisition
2008
Proceeding of the 2nd ACM workshop on Improving non english web searching - iNEWS '08
This work addresses the use of computational linguistic analysis techniques for conceptual graphs learning from unstructured texts. A technique including both content mining and interpretation, as well as clustering and data cleaning, is introduced. Our proposal exploits sentence structure in order to generate concept hypothese, rank them according to plausibility and select the most credible ones. It enables the knowledge acquisition task to be performed without supervision, minimizing the
doi:10.1145/1460027.1460032
dblp:conf/cikm/FernandezCF08
fatcat:cz3m3a7zvjedtiqdffn6bsjj3e