Placing search in context: the concept revisited
Proceedings of the 10th international conference on World Wide Web
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
Generic Command Interpretation Algorithms for Conversational Agents
IAT '06 Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology
Case-based techniques used for dialogue understanding and planning in a human-robot dialogue system
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
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This paper presents a new semantic relatedness measure on semantic networks (SN) that uses both hierarchical and non-hierarchical relations. Our approach relies on two assumptions. Firstly, in a given SN, only a few numbers of paths can be considered as “semantically correct” and these paths obey to a given set of rules. Secondly, following a given edge in a path has a cost (which depends on its type, is-a, part-of, etc.) and its position in the path. We propose an evaluation of our measure on WordNet with two different benchmarks, using the part-of relation. We show that, in this context, our measure does better than the classical semantic measures.