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Communication Dans Un Congrès Année : 2011

Invariants and variability of synonymy networks: Self mediated agreement by confluence

Résumé

Edges of graphs that model real data can be seen as judgements whether pairs of objects are in relation with each other or not. So, one can evaluate the similarity of two graphs with a measure of agreement between judges classifying pairs of vertices into two cate- gories (connected or not connected). When applied to synonymy networks, such measures demonstrate a surprisingly low agreement be- tween various resources of the same language. This seems to suggest that the judgements on synonymy of lexemes of the same lexi- con radically differ from one dictionary ed- itor to another. In fact, even a strong dis- agreement between edges does not necessarily mean that graphs model a completely differ- ent reality: although their edges seem to dis- agree, synonymy resources may, at a coarser grain level, outline similar semantics. To in- vestigate this hypothesis, we relied on shared common properties of real world data net- works to look at the graphs at a more global level by using random walks. They enabled us to reveal a much better agreement between dense zones than between edges of synonymy graphs. These results suggest that although synonymy resources may disagree at the level of judgements on single pairs of words, they may nevertheless convey an essentially simi- lar semantic information.

Domaines

Linguistique
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Dates et versions

hal-00992057 , version 1 (26-05-2016)

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  • HAL Id : hal-00992057 , version 1

Citer

Benoit Gaillard, Bruno Gaume, Emmanuel Navarro. Invariants and variability of synonymy networks: Self mediated agreement by confluence. TextGraphs-6 2011 : Graph-based Methods for Natural Language Processing, Jun 2011, Portland, United States. pp.50--62. ⟨hal-00992057⟩
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