Automatic Mapping Clinical Notes to Medical - RMIT University

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$journal of latex class files, vol. 6, no. 1, january ... - RMIT University$

plicitly matching the syntax of the target language, suggests that this is a source of the improvement obtained by the reordering approach of Collins et al. In future work we would like to implement the proposed reordering technique after correcting for the parser distortions, hopefully confirming the Collins results over the standard baseline for this language pair, and also confirming the relative improvement of the approach of this paper. 7 Conclusion Previous work has demonstrated that reordering of the text in the source language can lead to an improvement in machine translation quality. Earlier methods either tried to learn appropriate rules for reordering, or have used hand-coded rules that take account of specific differences between language pairs. In this work, we have explored how a claimed universal property of language — that there is a tendency to minimise the distance between a head and its dependents — can be adapted to automatically reorder constituents in the source language. This leads to an improvement in translation quality when the source language, Dutch, is one where this tendency is less present than in the target language English. We demonstrate that, in the Dutch-English case, unrestricted application of the head-dependent distance minimisation strategy is not optimal, and that a restricted version of the strategy does best; we show that this can achieve half of the improvement of the handcrafted rules by using only one languageindependent principle, and suggests that what is contributing to the improvement obtained in the reordering is the collapsing of elements into the phrasal window. References Gosse Bouma, Gertjan van Noord, and Robert Malouf. 2000. Alpino: Wide Coverage Computational Analysis of Dutch. In Computational Linguistics in the Netherlands (CLIN). Peter F. Brown, Stephen Della Pietra, Vincent J. Della Pietra, and Robert L. Mercer. 1994. The Mathematic 154 of Statistical Machine Translation: Parameter Estimation. Computational Linguistics, 19(2):263–311. Michael Collins, Philipp Koehn, and Ivona Kucerova. 2005. Clause restructuring for statistical machine translation. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL), pages 531–540, Ann Arbor, Michigan, June. Marta R. Costa-Juss and Jos A. R. Donollosa. 2006. Statistical Machine Reordering. In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, pages 70–76. J. A. Hawkins. 1990. A parsing theory of word order universals. Linguistic Inquiry, 21:223–261. Philipp Koehn, Franz Josef Och, and Daniel Marcu. 2003. Statistical phrase-based translation. In NAACL ’03: Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology, pages 48–54, Morristown, NJ, USA. Association for Computational Linguistics. Philipp Koehn. 2003. Europarl: A Multilingual Corpus for Evaluation of Machine Translation Philipp Koehn, Draft, Unpublished. Philip Koehn. 2004. Pharaoh: a Beam Search Decoder for Phrase-Based Statistical Machine Translation Models, Philipp Koehn, AMTA. Franz Josef Och and Hermann Ney. 2003. A systematic comparison of various statistical alignment models. Computational Linguistics, 29(1):19–51. Kishore Papineni, Salim Roukos, Todd Ward, and Wei- Jing Zhu. 2002. Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40 th Annual Meeting of the Association for Computational Linguistics (ACL), pages 311–318, Jul. Chris Quirk, Arul Menezes, and Colin Cherry. 2005. Dependency treelet translation: Syntactically informed phrasal SMT. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL’05), pages 271–279, Ann Arbor, Michigan, June. Association for Computational Linguistics. A. Stolcke. 2002. SRILM – an extensible language modeling toolkit. In Proceedings Intl. Conf. on Spoken Language Processing, volume 2, pages 901–904. Joseph P. Turian, Luke Shen, and I. Dan Melamed. 2003. Evaluation of machine translation and its evaluation. In Proceedings of MT Summit IX. Fei Xia and Michael McCord. 2004. Improving a statistical MT system with automatically learned rewrite patterns. In Proceedings of the 20th International Conference on Computational Linguistics (Coling), pages 508–514.
Analysis and Prediction of User Behaviour in a Museum Environment Abstract I am a student at the University of Melbourne, my supervisors are Timothy Baldwin and Steven Bird. The full submission will be submitted later, abstract follows. The prolific distribution and continued evolution of portable technology has had a marked effect of how we as human beings live our lives. But the inter-relation between the technological virtual environment and the physical space where we live is less prominent. Using technology such as mobile phones and other portable handheld devices, we can bring information about the surrounding environment directly to the people inhabiting this environment; us. Building a predictive model allows us to anticipate future actions the person may take. This can be then used as a navigation aid, planning for future paths, or modifying any information presented to the user to take into account their predisposition towards elements of the environment. By using a person’s history within the environment, and information associated with each item in the history, accurate predictions can be made as to what the person will visit in the future. One can consider the elements in the person’s history as a vocabulary of previseted locations, and can hence use language modelling techniques to predict future locations. This study compares and analyses different methods of path prediction including, Naive Bayes, document similarity, visitor feedback and different measures of lexical similarity. Karl Grieser BSc.(Hons) student University of Melbourne k.grieser@gmail.com Proceedings of the 2006 Australasian Language Technology Workshop (ALTW2006), pages 155–155. 155
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