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Thursday 6 December 2012 09:00–10:00 Invited talk (Owheo 206; Chair: Timothy Baldwin) Chris Brockett Diverse Words, Shared Meanings: Statistical Machine Translation for Paraphrase, Grounding, and Intent 10:00–10:30 Coffee Session 4: ALTA/ADCS shared session (Owheo 106; Chair: Alistair Knott) 10:30–11:00 ADCS paper Lida Ghahremanloo, James Thom and Liam Magee An Ontology Derived from Heterogeneous Sustainability Indicator Set Documents 11:00–11:30 ADCS paper Bevan Koopman, Peter Bruza, Guido Zuccon, Michael John Lawley and Laurianne Sitbon Graph-based Concept Weighting for Medical Information Retrieval 11:30–12:00 Abeed Sarker, Diego Mollá-Aliod and Cecile Paris Towards Two-step Multi-document Summarisation for Evidence Based Medicine: A Quantitative Analysis 12:00–12:30 Alex G. Smith, Christopher X. S. Zee and Alexandra L. Uitdenbogerd In Your Eyes: Identifying Clichés in Song Lyrics 12:30–14:00 Lunch Session 5: ALTA Shared Task and poster boasters (Owheo 206; Chair: Karin Verspoor) 14:00–14:30 Iman Amini, David Martinez and Diego Molla ALTA 2012 Shared Task overview 14:30–14:50 ALTA poster boasters Paul Cook and Marco Lui langid.py for better language modelling Robert Fromont and Jennifer Hay LaBB-CAT: an Annotation Store Jenny Mcdonald, Alistair Knott and Richard Zeng Free-text input vs menu selection: exploring the difference with a tutorial dialogue system. Jared Willett, Timothy Baldwin, David Martinez and Angus Webb Classification of Study Region in Environmental Science Abstracts ALTA Shared Task poster boasters Marco Lui Feature Stacking for Sentence Classification in Evidence-based Medicine Abeed Sarker Multi-class classification of medical sentences using SVMs 14:50–15:00 Awards and final remarks (Owheo 206) 15:00–15:30 Coffee 15:30–17:00 Poster session with ADCS (Owheo 106) 19:30–21:30 Boat trip: Meet at 19:00 at the wharf, 20 Fryatt St. VI
Contents Invited talks 1 Using a large annotated historical corpus to study word-specific effects in sound change Jennifer Hay 2 Diverse Words, Shared Meanings: Statistical Machine Translation for Paraphrase, Grounding, and Intent Chris Brockett 3 <strong>Full</strong> papers 4 A Citation Centric Annotation Scheme for Scientific Articles Angrosh M.A., Stephen Cranefield and Nigel Stanger 5 Semantic Judgement of Medical Concepts: Combining Syntagmatic and Paradigmatic Information with the Tensor Encoding Model Michael Symonds, Guido Zuccon, Bevan Koopman, Peter Bruza and Anthony Nguyen 15 Active Learning and the Irish Treebank Teresa Lynn, Jennifer Foster, Mark Dras and Elaine Uí Dhonnchadha 23 Unsupervised Estimation of Word Usage Similarity Marco Lui, Timothy Baldwin and Diana McCarthy 33 Valence Shifting: Is It A Valid Task? Mary Gardiner and Mark Dras 42 Experimental Evaluation of a Lexicon- and Corpus-based Ensemble for Multi-way Sentiment Analysis Minh Duc Cao and Ingrid Zukerman 52 Segmentation and Translation of Japanese Multi-word Loanwords James Breen, Timothy Baldwin and Francis Bond 61 Measurement of Progress in Machine Translation Yvette Graham, Timothy Baldwin, Aaron Harwood, Alistair Moffat and Justin Zobel 70 Towards Two-step Multi-document Summarisation for Evidence Based Medicine: A Quantitative Analysis Abeed Sarker, Diego Mollá-Aliod and Cecile Paris 79 In Your Eyes: Identifying Clichés in Song Lyrics Alex G. Smith, Christopher X. S. Zee and Alexandra L. Uitdenbogerd 88 Free-text input vs menu selection: exploring the difference with a tutorial dialogue system. Jenny Mcdonald, Alistair Knott and Richard Zeng 97 Short papers 106 VII
Page 1 and 2: Australasian Language Technology As
Page 3 and 4: ALTA 2012 Workshop Committees Works
Page 5: ALTA 2012 Programme The proceedings
Page 9 and 10: Invited talks 1
Page 11 and 12: Diverse Words, Shared Meanings: Sta
Page 13 and 14: A Citation Centric Annotation Schem
Page 15 and 16: The structure of this paper is as f
Page 17 and 18: understanding of sentences surround
Page 19 and 20: henceforth referred to as Annotator
Page 21 and 22: References Angrosh, M A, Cranefield
Page 23 and 24: Semantic Judgement of Medical Conce
Page 25 and 26: 2012). The TE model provides a form
Page 27 and 28: Correlation coefficient with human
Page 29 and 30: Pair # Concept 1 Doc. Freq. Concept
Page 31 and 32: Active Learning and the Irish Treeb
Page 33 and 34: 2.2 Sources of annotator disagreeme
Page 35 and 36: complement (csubj) 2 . See Figure 4
Page 37 and 38: top Y trees from this ordered set a
Page 39 and 40: References Ron Artstein and Massimo
Page 41 and 42: Unsupervised Estimation of Word Usa
Page 43 and 44: not lend itself to determining unsu
Page 45 and 46: T 0: think, want, thing, look, tell
Page 47 and 48: correlation is much stronger than t
Page 49 and 50: References Eneko Agirre and Philip
Page 51 and 52: eaders with sentences with a negati
Page 53 and 54: Question Which word is closest in m
Page 55 and 56: Acceptability and negativity: conce
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MORE NEGATIVE / LESS NEGATIVE MR Δ
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Julie Elizabeth Weeds. 2003. Measur
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cation produced by a supervised mac
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understood to carry a lower weight
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Figure 1: Average classification ac
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0.8 0.75 0.7 AuthorA4 AuthorB4 Auth
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Segmentation and Translation of Jap
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tomatosōsu “tomato sauce”, rev
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“markup” and “Mach”, so the
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MWE Segmentation Possible Translati
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English Term Pairs from Search Engi
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techniques used are, of necessity,
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ation metrics robust, if they are v
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Figure 2: Methodologies of human as
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an optimal method? Machine translat
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Towards Two-step Multi-document Sum
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archical and non-hierarchical relat
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We use the MetaMap 7 tool to automa
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T T & C CC z -1.5 -1.27 -1.33 p-val
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References Alan R. Aronson. 2001. E
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techniques and results are shown. F
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Rock Hip-Hop Electronic Punk Metal
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Rank Frequency Frequency (filtered)
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Ex. 1 Ex. 2 Ex. 3 Score Song Title
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Free-text input vs menu selection:
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consistent with the much earlier ed
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3.2 Dialogue system architecture Th
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Control Free-text Menu-based n=119
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tions in analyzing algebra example
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langid.py for better language model
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documents of MIME type text/html wi
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Acknowledgments NICTA is funded by
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LaBB-CAT: an Annotation Store Rober
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elationship between the coincidence
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Communication 33 (special issue on
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matically extracting location infor
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Classifier DBp:1R Geo:1R D+G:1R DBp
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ALTA Shared Task papers 123
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All Struct. Unstruct. Total - Abstr
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System Population Intervention Back
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tence positions (absolute and relat
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sitional attributes, and sequential
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ordering labels, All includes BOW,
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3 Software Used All experimentation
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Combination Output Public Private C
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Experiments with Clustering-based F
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3 Results For the initial experimen
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