Supporting collocation learning with a digital library

Abstract

Extensive knowledge of collocations is a key factor that distinguishes learners from fluent native speakers. Such knowledge is difficult to acquire simply because there is so much of it. This paper describes a system that exploits the facilities offered by digital libraries to provide a rich collocation-learning environment. The design is based on three processes that have been identified as leading to lexical acquisition: noticing, retrieval and generation. Collocations are automatically identified in input documents using natural language processing techniques and used to enhance the presentation of the documents and also as the basis of exercises, produced under teacher control, that amplify students' collocation knowledge. The system uses a corpus of 1.3 B short phrases drawn from the Web from which 29 M collocations have been automatically identified. It also connects to examples garnered from the live Web and the British National Corpus.Keywords: CALL, collocation learning, collocation activities, automatic answer generation, cherry-picking INTRODUCTIONWhy do language learners find it difficult to differentiate between words like look, see and watch, or broad and wide? Why do students who know many individual words still struggle to express complex ideas simply and precisely? Why are so many frustrated that they make little visible progress? How is it that native speakers communicate so much more effectively? The answers rest on the collocational knowledge of language learners. It is the collocates of look, see and watch or broad and wide that reveal their different shades of meaning, rather than their dictionary definitions (Conzett, 2000). Complex ideas are hard to express unless one can use simple vocabulary in a range of collocations (Lewis, 1993). Hill (1999) points out that students with good ideas often lose marks because they don't know the four or five most important collocations of a key word that is central to what they are writing about. Wray (2002) emphasizes that collocations are particularly important for learners striving for a high degree of competence in a second language, because they enhance not only accuracy but also fluency. Nesselhauf (2003, p.223) reiterates, -Collocations are of particular importance for learners striving for a high degree of competence in the second language but they are also of importance for learners with less ambitious aspirations, as they not only enhance accuracy but also fluency‖.

DACE: Extracting and Exploring Large Scale Chinese Web Collocations with Distributed Computing

“…Table 5 lists the top collocations extracted by different measures. Compared to previous study on the English language [24], similar behavior of the three measures was observed. In general, 2 -test and mutual information tend to favor expressions with low frequency and has a repetitive pattern.…”

“…assuming independent events). Such tests include comparing the log-likelihood ratio [12], t-test [13] and 2 -test [8]. Besides, position, span and syntactic rules can also be considered in the association measure [14].…”

“…Table 1 shows that news corpus was by far the major resource for most automatic collocation extraction systems. Recently in the English language domain, large-scale web resources and multilingual copora have also been used [8,17]. They provide unprecedented affluent resources for the task.…”

“…This include, for example, compound nouns like train station, phrasal verbs like follow up, proper nouns like New Zealand, and common syntactic patterns like adjective+noun and heavy rain. Collocations have been used widely in many natural language processing tasks, for example to help natural language generation [4], improve machine translation quality [1], impact search result ranking [5], disambiguate word senses [6] and assist sentiment analysis [7] and second language learning [8].…”

“…Previous researchers propose to exploit the enormous web resources to discover collocations for language learning [8]. This motivates us to tap into the Chinese web 5-gram corpus [9] for identifying Chinese collocations.…”