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Australasian Language Technology Association Workshop 2012 (ALTA 2012) http://www.alta.asn.au/events/alta2012 Sponsors: Volume 10, 2012 ISSN: 1834-7037 II
ALTA 2012 Workshop Committees Workshop Co-Chairs • Paul Cook (The University of Melbourne) • Scott Nowson (Appen Butler Hill) Workshop Local Organiser • Alistair Knott (University of Otago) Programme Committee • Timothy Baldwin (University of Melbourne) • Lawrence Cavedon (NICTA and RMIT University) • Nathalie Colineau (CSIRO - ICT Centre) • Rebecca Dridan (University of Oslo) • Alex Chengyu Fang (The City University of Hong Kong) • Nitin Indurkhya (UNSW) • Jong-Bok Kim (Kyung Hee University) • Alistair Knott (University of Otago) • Oi Yee Kwong (City University of Hong Kong) • Francois Lareau (Macquarie University) • Jey Han Lau (University of Melbourne) • Fang Li (Shanghai Jiao Tong University) • Haizhou Li (Institute for Infocomm Research) • Marco Lui (University of Melbourne) • Ruli Manurung (Universitas Indonesia) • David Martinez (NICTA VRL) • Tara McIntosh (Wavii) • Meladel Mistica (The Australian National University) • Diego Mollá (Macquarie University) • Su Nam Kim (Monash University) • Luiz Augusto Pizzato (University of Sydney) • David Powers (Flinders University) • Stijn De Saeger (National Institute of Information and Communications Technology) • Andrea Schalley (Griffith University) • Rolf Schwitter (Macquarie University) • Tony Smith (Waikato University) • Virach Sornlertlamvanich (National Electronics and Computer Technology Center) • Hanna Suominen (NICTA) • Karin Verspoor (National ICT Australia) III
Page 1: Australasian Language Technology As
Page 5 and 6: ALTA 2012 Programme The proceedings
Page 7 and 8: Contents Invited talks 1 Using a la
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
Page 59 and 60:
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
Page 75 and 76:
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
Page 121 and 122:
LaBB-CAT: an Annotation Store Rober
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elationship between the coincidence
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Communication 33 (special issue on
Page 127 and 128:
matically extracting location infor
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Classifier DBp:1R Geo:1R D+G:1R DBp
Page 131 and 132:
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
Page 147 and 148:
Experiments with Clustering-based F
Page 149 and 150:
3 Results For the initial experimen
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