[PDF] Top 20 A Graph Model for Unsupervised Lexical Acquisition

... Various cutoff functions were used to deter- mine how many times a relationship must be observed to be counted as a link in the graph. A well-behaved option was to take the top n neighbours of each word, where n ... See full document

... inducing lexical categories, the second one has tackled the problem from a more global perspective, inducing categories – not necessarily syntactic – and evaluating them using other lin- guistic tasks (Frank et ... See full document

... We therefore evaluate our system in two ways. First, we compare its output, as well as the output of a number of clustering baselines, to the gold standard annotation of corpora from two differ- ent domains (the only ... See full document

... realistic model of early language acquisition should propose a method of inferring the intended forms (Figure 1a) from the unsegmented surface forms (1c) while also learning a model of phonetic ... See full document

... different graph-based mod- els over two well known WSD benchmarks is re- ...surfer model as defined by PageRank model (Brin and Page, 1998) are ...employed lexical information and the overall ... See full document

... an unsupervised categorization ...an unsupervised categoriza- tion model has the disadvantage of favoring one set of principles and intuitions over another; that is, assuming that there is a correct ... See full document

... an unsupervised word- topic graph model, which represents and measures the word importance by using contex- tual information from both lexical and topical ... See full document

... There have been various approaches to unsuper- vised PoS induction. One such approach, reported in (Brown et al., 1992) is based on the class based n-gram models. In (Clark, 2003) distributional and morphological ... See full document

... Data-oriented parsing (Bod et al., 2003) shares basic assumptions about linguistic inference with exemplar-based theory, but it does not model or use the similarity between input and stored exemplars. Previous ... See full document

... NTF model to a simple non-negative matrix factorization ( NMF ) model, com- parable to the unsupervised model presented by Rooth et ...this model, a matrix was constructed that contains ... See full document

... trigram model from the above equation is able to correctly choose the correct tag since all P ( w | t i ) are ...lexicon acquisition, described in the next section, addresses this very ... See full document

... This is perhaps not surprising. After all, it’s not clear that there is any principled way of determining which words are contained in these respective vocabularies. The logical vocabulary is made up of those words that ... See full document

... The source language features that revealed the sim- ilarity of the translations and served to their cluster- ing (cf. section 3) can be exploited by an unsuper- vised WSD classifier (Apidianaki, 2009). In order to ... See full document

... improves lexical learning—we use a similar idea in this ...the lexical storage of com- plete ...2008b). Unsupervised Lexicon Discovery In contrast to models of spoken term discovery and word segmen- ... See full document

... 7 Precision is the number of detected correct esl's over the total number of detected esl's, while recall is the number of detected correct esl's over the number of cor- rect esl~s.. Paz[r] ... See full document

... Finally, we explore a number of ways to com- bine lexicons directly. The motivation for this is that the lexicons have different strengths and weaknesses, representing partially independent information. An obvious method ... See full document

... proposed model are detailed in Table 1. Overall we observe that our model achieves the best results and significantly outperforms the baselines on most ... See full document

... Role of Word Sense Disalnbiguation in Lexical Acquisition Predicting Semantics from Syntactic Cues Role of Word Sense Disambiguation in Lexical Acquisition Predicting Semantics from Syntactic Cues B o[.] ... See full document

... We evaluate our phonetic clustering by comput- ing the same pairwise F-score on pairs of vowel to- kens. Our score is 83%; the Feldman et al. (2013a) model scores 76%. We conjecture that the improve- ment results ... See full document

... evaluate acquisition of predominance information we have used publicly available gold-standard sense-tagged corpora, and these have WordNet ...Senseval-2 lexical sample are not discovered, including the ... See full document