Automatic Mapping Clinical Notes to Medical - RMIT University

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References Jennifer Arnold, Janet Eisenband, Sarah Brown- Schmidt, and John Trueswell. 2000. The rapid use of gender information: evidence of the time course of pronoun resolution from eyetracking. Cognition, 76:B13–B26. Julie Boland, M. Acker, and L. Wagner. 1998. The use of gender features in the resolution of pronominal anaphora. Cognitive Science Technical Report 17, The Ohio State University Center for Cognitive Science. Morton Ann Gernsbacher and D. Hargreaves. 1988. Accessing sentence participants: The advantage of first mention. Journal of Memory and Language, 27:699–717. Talmy Givón. 1983. Topic continuity in discourse: An introduction. In Talmy Givón, editor, Topic Continuity in Discourse: A Quantitative Cross-Language Study, pages 1–42. John Benjamins, Amsterdam. Peter Gordon, Barbara Grosz, and Laura Gilliom. 1993. Pronouns, names, and the centering of attention in discourse. Cognitive Science, 17:311–347. Barbara Grosz and Candace Sidner. 1986. Attention, intentions, and the structure of discourse. Computational Linguistics, 12:175–204. Barbara Grosz, A. Joshi, and S. Weinstein. 1995. Centering: A framework for modeling the local coherence of discourse. Computational Linguistics, 21:203–225. Irene Heim. 1982. The Semantics of Definite and Indefinite Noun Phrases. Ph.D. thesis, University of Massachusetts, Amherst. Graeme Hirst. 1981. Anaphora in Natural Language Understanding: A Survey. Springer-Verlag, Berlin. Jerry Hobbs. 1978. Resolving pronoun references. Lingua, 44:311–338. Susan Hudson-D’Zmura and Michael Tanenhaus. 1997. Assigning antecedents to ambiguous pronouns: The role of the center of attention as the default assignment. In M. Walker, A. Joshi, and Ellen Prince, editors, Centering Theory in Discourse, pages 199–226. Clarendon Press, Oxford. Ray Jackendoff. 1972. Semantic Interpretation in Generative Grammar. MIT Press, Cambridge, MA. Lauri Karttunen. 1976. Discourse referents. In James McCawley, editor, Syntax and Semantics, Vol. 7: Notes from the Linguistic Underground, pages 363– 385. Academic Press, New York. Andrew Kehler. 2002. Coherence, Reference, and the Theory of Grammar. CSLI Publications, Stanford University, CA. 96 Chris Kennedy and Branamir Boguraev. 1996. Anaphora for everyone: Pronominal anaphora resolution without a parser. In Proceedings of the 16th International Conference on Computational Linguistics (COLING ’96), pages 113–118, Copenhagen, Denmark. Shalom Lappin and Herbert Leass. 1994. An algorithm for pronominal anaphora resolution. Computational Linguistics, 20:535–561. Richard Larson. 1988. On the double object construction. Linguistic Inquiry, 19:335–392. Beth Levin. 1993. English Verb Classes and Alternations: A Preliminary Investigation. University of Chicago Press, Chicago, IL. Alison Mathews and Martin Chodorow. 1988. Pronoun resolution in two-clause sentences: Effects of ambiguity, antecedent location, and depth of embedding. Journal of Memory and Language, 27:245– 260. Ruslan Mitkov. 2002. Anaphora Resolution. Longman, London. Vincent Ng and Clarie Cardie. 2002. Improving machine learning approaches to coreference resolution. In Proceedings of the 40 th Annual Meeting of the Association for Computational Linguistics (ACL), pages 104–111, Philadelphia, PA. Malka Rappaport and Beth Levin. 1988. What to do with θ-roles. In Wendy Wilkins, editor, Syntax and Semantics 21: Thematic Relations, pages 7–36. Academic Press, New York. Ralph Rose. 2005. The Relative Contribution of Syntactic and Semantic Prominence to the Salience of Discourse Entities. Ph.D. thesis, Northwestern University. Wee Meng Soon, Hwee Tou Ng, and Daniel Chung Yong Lim. 2001. A machine learning approach to coreference resolution of noun phrases. Computational Linguistics, 27:521–544. Margaret Speas. 1990. Phrase Structure in Natural Language. Kluwer Academic Publishers, Dordrecht, Netherlands. Rosemary Stevenson, Rosalind Crawley, and David Kleinman. 1994. Thematic roles, focus and the representation of events. Language and Cognitive Processes, 9:519–548. Rosemary Stevenson, Alistair Knott, Jon Oberlander, and Sharon McDonald. 2000. Interpreting pronouns and connectives: Interactions among focusing, thematic roles and coherence relations. Language and Cognitive Processes, 15(3):225–262. Carol Tenny. 1994. Aspectual Roles and the Syntax- Semantics Interface. Kluwer Academic Publishers, Dordrecht, Netherlands.
Web Readability and Computer-Assisted Language Learning Alexandra L. Uitdenbogerd School of Computer Science and Information Technology RMIT University Melbourne, Australia Abstract Proficiency in a second language is of vital importance for many people. Today’s access to corpora of text, including the Web, allows new techniques for improving language skill. Our project’s aim is the development of techniques for presenting the user with suitable web text, to allow optimal language acquisition via reading. Some text found on the Web may be of a suitable level of difficulty but appropriate techniques need to be devised for locating it, as well as methods for rapid retrieval. Our experiments described here compare the range of difficulty of text found on the Web to that found in traditional hard-copy texts for English as a Second Language (ESL) learners, using standard readability measures. The results show that the ESL text readability range fall within the range for Web text. This suggests that an on-line text retrieval engine based on readability can be of use to language learners. However, web pages pose their own difficulty, since those with scores representing high readability are often of limited use. Therefore readability measurement techniques need to be modified for the Web domain. 1 Introduction In an increasingly connected world, the need and desire for understanding other languages has also increased. Rote-learning and grammatical approaches have been shown to be less effective than communicative methods for developing skills in using language (Higgins, 1983; Howatt, 1984; Kellerman, 1981), therefore students who need to be able to read in the language can benefit greatly from extensively reading material at their level of skill (Bell, 2001). This reading material comes from a variety of sources: language learning textbooks, reading books with a specific level of vocabulary and grammar, native language texts, and on-line text. There is considerable past work on measuring the readability of text, however, most of it was originally intended for grading of reading material for English-speaking school children. The bulk of readability formulae determined from these studies incorporate two main criteria for readability: grammatical difficulty — usually estimated by sentence length, and vocabulary difficulty, which is measured in a variety of ways (Klare, 1974). Publishers later decided to use the readability measures as a guideline for the writing of texts, with mixed success. However, new reading texts catering for foreign language learners of various languages are still being published. Most of these use specific vocabulary sizes as the main criterion for reading level. Others are based on specific language skills, such as the standard developed by the European community known as the “Common European Framework of Reference for Languages” (COE, 2003). The goal of our research is to build an application that allows the user to improve their language skills through accessing appropriate reading material from the Web. This may incorporate personalised retrieval based on a user’s level of skill in the target language, first language and specific vocabulary of interest. Greater detail about the application’s requirements and potential implementation issues are discussed elsewhere (Uitdenbogerd, 2003). Proceedings of the 2006 Australasian Language Technology Workshop (ALTW2006), pages 97–104. 97
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Proceeding of the Australasian Lang
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Program Chairs: Committees Lawrence
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Towards the Evaluation of Referring
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Figure 2: Cells affected by adding
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were used because the accuracy for
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TIME ACC COVER FAIL RATE % secs % %
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model. We explore different estimat
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S.S. Source Sense Source S.S. Acc.
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acy. The difference in correctly as
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Experiments with Sentence Classific
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datasets with skewed distribution t
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words produced by the feature selec
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Sentence Class NB DT SVM Apology 1.
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Computational Semantics in the Natu
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Any string which cannot be decompos
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satisfy(Formula,model(D,F),G,pos):n
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Classifying Speech Acts using Verba
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The principles are dichotomous —
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ance. Several additional example ut
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our results. In classifying only th
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Word Relatives in Context for Word
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create a collection of training exa
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Page 86 and 87: References Aronson, A. R. (2001). E
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References Timothy Baldwin and Fran
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dependencies in German with respect
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a brevity penalty of BLEU n = 1 n =
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plicitly matching the syntax of the
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Probabilities improve stress-predic
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Towards Cognitive Optimisation of a
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Natural Language Processing and XML
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Extracting Patient Clinical Profile
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Automatic Mapping Clinical Notes to Medical - RMIT University

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