This paper presents a graph-theoretic model of the acquisition of lexical syntactic representations. The representations the model learns are non-categorical or graded. We propose...
We propose a range of deep lexical acquisition methods which make use of morphological, syntactic and ontological language resources to model word similarity and bootstrap from a ...
This paper presents an unsupervised method for assembling semantic knowledge from a part-ofspeech tagged corpus using graph algorithms. The graph model is built by linking pairs o...
This paper presents a computational model ofverb acquisitionwhich uses what we willcallthe principle of structured overeommitment to eliminate the need for negative evidence. The ...
Lexical Attraction Models (LAMs) were first introduced by Deniz Yuret in (Yuret 1998) to exemplify how an algorithm can learn word dependencies from raw text. His general thesis i...