Acronym-Meaning Extraction from Corpora Using Multi-Tape Weighted Finite-State Machines

The automatic extraction of acronyms and their meaning from corpora is an important sub-task of text mining. It can be seen as a special case of string alignment, where a text chunk is aligned with an acronym. Alternative alignments have different cost, and ideally the least costly one should give the correct meaning of the acronym. We show how this approach can be implemented by means of a 3-tape weighted finite-state machine (3-WFSM) which reads a text chunk on tape 1 and an acronym on tape 2, and generates all alternative alignments on tape 3. The 3-WFSM can be automatically generated from a simple regular expression. No additional algorithms are required at any stage. Our 3-WFSM has a size of 27 states and 64 transitions, and finds the best analysis of an acronym in a few milliseconds.Comment: 6 pages, LaTe

Individual differences in adult second language learning: a cognitive perspective

What makes some people more successful language learners than others? Scholars and practitioners of adult second language learning traditionally have cast the issue of individual differences in terms of such constructs as aptitude, motivation, learning strategies, learning styles, meta-linguistic awareness, and personality traits (e.g., extraversion), as well as a range of other social and affective variables (Ehrman, Leaver & Oxford, 2003). These are complex constructs that often lack a clear description of the underlying mechanisms. In this short overview we will take a cognitive perspective and link individual differences in adult L2 learning to individual differences in cognitive abilities. Examining cognitive factors that are predictive of L2-learning success can help to illuminate the mechanisms that underlie the learning process. At the same time, recognising and understanding the links between cognitive abilities and language learning may help teachers and learners to adjust their teaching methods and the learning environment in ways that are beneficial to individual learners. Although we are still far from being able to make specific evidence-based recommendations, reviewing what is known about cognitive predictors of successful language learning may be a useful start