In this paper, we introduce a hybrid method to associate English collocations with sense class members chosen from WordNet. Our combinational approach includes a learning-based method, a paraphrase-based method and a sense frequency ranking method. At training time, a set of collocations with their tagged senses is prepared. We use the sentence information extracted from a large corpus and cros...

In this paper we discuss the problem of discovering interesting word sequences in the light of two traditions: sequential pattern mining (from data mining) and collocations discovery (from computational linguistics). Smadja (1993) defines a collocation as “a recurrent combination of words that cooccur more often than chance and that correspond to arbitrary word usages.” The notion of arbitrarin...

This paper describes a corpus-based contrastive study of collocation in English and Chinese. In light of the corpus-based approach to identify functionally equivalent units, the present paper attempts to identify the collocational translation equivalents of zunshou by using a parallel corpus and two comparable corpora. This study shows that more often than not, we can find in English more than ...

One of the most common lexical misuse problems in the second language context concerns near synonyms. Dictionaries and thesauri often overlook the nuances of near synonyms and make reference to near synonyms in providing definitions. The semantic differences and implications of near synonyms are not easily recognized and often fail to be acquired by L2 learners. This study addressed the distinc...

Adaptor grammars (Johnson et al., 2007b) are a non-parametric Bayesian extension of Probabilistic Context-Free Grammars (PCFGs) which in effect learn the probabilities of entire subtrees. In practice, this means that an adaptor grammar learns the structures useful for generating the training data as well as their probabilities. We present several different adaptor grammars that learn to segment...

We present an experimental study of how different features help measuring the idiomaticity of noun+verb (NV) expressions in Basque. After testing several techniques for quantifying the four basic properties of multiword expressions or MWEs (institutionalization, semantic non-compositionality, morphosyntactic fixedness and lexical fixedness), we test different combinations of them for classifica...

In this paper, we present machine learning approach for the classification indirect anaphora in Hindi corpus. The direct anaphora is able to find the noun phrase antecedent within a sentence or across few sentences. On the other hand indirect anaphora does not have explicit referent in the discourse. We suggest looking for certain patterns following the indirect anaphor and marking demonstrativ...

Collocation is a popular method in geodesy for combining heterogeneous data of different kind. It comprises adjustment, interpolation and extrapolation as special cases. Current methods of collocation apply however only if the trend parameters are real valued. In the present contribution we will generalize the theory of collocation by permitting the trend parameters to be integer valued. It wil...

This paper presents the design and construction of an annotated Chinese collocation bank as the resource to support systematic research on Chinese collocations. With the help of computational tools, the bi-gram and n-gram collocations corresponding to 3,643 headwords are manually identified. Furthermore, annotations for bi-gram collocations include dependency relation, chunking relation and cla...

In this paper we present a new method of automatic collocation identification. Collocation is an important relation between words, which is widely used, among others, in information retrieval tasks. Over the last years, many methods of automatic collocation acquisition from text corpora have been proposed. The approach described in this paper differs from the others by focusing on domain colloc...