In this paper we propose a system for the recommendation of tagged pictures obtained from the Web. The system, driven by user feedback, executes an abductive reasoning (based on WordNet synset semantic relations) that is able to iteratively lead to new concepts which progressively represent the cognitive creative user state. Furthermore we design a selection mechanism to pick the most relevant abductive inferences by mixing a topological graph analysis together with a semantic similitude measure.
CitationLopes, J.; Alvarez-Napagao, Sergio; Vazquez-Salceda, J. "Word sense ranking based on semantic similarity and graph entropy". 2009.
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder. If you wish to make any use of the work not provided for in the law, please contact: firstname.lastname@example.org