A pretopological framework for the automatic construction of lexical-semantic structures from texts

Abstract : We present in this paper a new approach for the automatic generation of lexical structures from texts. This tedious task is based on the strong hypothesis that simple statistical observations on textual usages can provide pieces of semantics about the lexicon. Using such "naive" observations only, we propose a (pre)-topological framework to formalize and combine various hypothesis on textual data usages and then to derive a structure similar to usual lexical knowledge basis such as WordNet. In addition we also consider the evaluation problem for obtained lexical structures ; a multi-level evaluation strategy is proposed that measures the fitting between a given reference structure and automatically generated structures on different point of views : intrinsic/structural and application-based points of view. The evaluation strategy is then used to quantify the contribution of the new structuring approach with respect to the corresponding solution proposed by (Sanderson et al. 2000) on two case studies that differs on the domain and the size of the lexicon.
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Guillaume Cleuziou, Davide Buscaldi, Vincent Levorato, Gaël Dias. A pretopological framework for the automatic construction of lexical-semantic structures from texts. CIKM 2011, Oct 2011, Glasgow, United Kingdom. pp.2453-2456, ⟨10.1145/2063576.2063990⟩. ⟨hal-00825232⟩

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