Scott S. L. Piao

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In this paper, we report on our experiment to extract Chinese multiword expressions from corpus resources as part of a larger research effort to improve a machine translation (MT) system. For existing MT systems, the issue of multiword expression (MWE) identification and accurate interpretation from source to target language remains an unsolved problem. Our(More)
As a part of the METER (MEasuring TExt Reuse) project we have built a new type of comparable corpus consisting of annotated examples of related newspaper texts. Texts in the corpus were manually collected from two main sources: the British Press Association (PA) and nine British national newspapers that subscribe to the PA newswire service. In addition to(More)
In this paper we present the METER Corpus, a novel resource for the study and analysis of journalistic text reuse. The corpus consists of a set of news stories written by the Press Association (PA), the major UK news agency, and a set of stories about the same news events, as published in various British newspapers. In some cases the newspaper stories are(More)
Automatic extraction of multiword expressions (MWE) presents a tough challenge for the NLP community and corpus linguistics. Although various statistically driven or knowledge-based approaches have been proposed and tested, efficient MWE extraction still remains an unsolved issue. In this paper, we present our research work in which we tested approaching(More)
Semantic lexical resources play an important part in both linguistic study and natural language engineering. In Lancaster, a large semantic lexical resource has been built over the past 14 years, which provides a knowledge base for the USAS semantic tagger. Capturing semantic lexicological theory and empirical lexical usage information extracted from(More)
This paper reports on an experiment in which we explore a new approach to the automatic measurement of multi-word expression (MWE) compositionality. We propose an algorithm which ranks MWEs by their compositionality relative to a semantic field taxonomy based on the Lancaster English semantic lexicon (Piao et al., 2005a). The semantic information provided(More)
Term extraction algorithms have various applications in Digital Economy research with the rise of online sources. This paper reports on an evaluation of five term extraction algorithms for automatic concept extraction in the musicology domain, which is carried out in the context of the RCUK funded SerenA Project. Our focus here is to identify the algorithms(More)
The METER (MEasuring TExt Reuse) corpus is a corpus designed to support the study and analysis of journalistic text reuse. It consists of a set of news stories written by the Press Association (PA), the major UK news agency, and a set of stories about the same news events, as published in various British newspapers, some of which were derived from the PA(More)