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| "abstract": [], | |
| "body_text": [ | |
| { | |
| "text": "\u2022 Stephen Wan (Data61)", | |
| "cite_spans": [], | |
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| "eq_spans": [], | |
| "section": "ALTA 2017 Workshop Committees Workshop Chairs", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "\u2022 Jojo Sze-Meng Wong (Monash University)", | |
| "cite_spans": [], | |
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| "eq_spans": [], | |
| "section": "ALTA 2017 Workshop Committees Workshop Chairs", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "\u2022 Jojo Sze-Meng Wong (Monash University)", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
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| "section": "Workshop Programme Chairs", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "\u2022 Gholamreza Ha ari (Monash University) Programme Committee ", | |
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| { | |
| "start": 20, | |
| "end": 39, | |
| "text": "(Monash University)", | |
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| "section": "Workshop Programme Chairs", | |
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| { | |
| "text": "This volume contains the papers accepted for presentation at the Australasian Language Technology Association Workshop (ALTA) 2017, held at Queensland University of Technology in Brisbane, Australia on 6-8 December 2017.", | |
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| "section": "Preface", | |
| "sec_num": null | |
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| { | |
| "text": "The goals of the workshop are to:", | |
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| "section": "Preface", | |
| "sec_num": null | |
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| "text": "\u2022 bring together the Language Technology (LT) community in the Australasian region and encourage interactions and collaboration; \u2022 foster interaction between academic and industrial researchers, to encourage dissemination of research results; \u2022 provide a forum for students and young researchers to present their research;", | |
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| "text": "\u2022 facilitate the discussion of new and ongoing research and projects;", | |
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| "section": "Preface", | |
| "sec_num": null | |
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| { | |
| "text": "\u2022 increase visibility of LT research in Australasia and overseas and encourage interactions with the wider international LT community.", | |
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| "section": "Preface", | |
| "sec_num": null | |
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| "text": "This year's ALTA Workshop presents 13 peer-reviewed papers, including 10 long papers and 3 short papers. We received a total of 23 submissions for long and short papers. Each paper was reviewed by three members of the program committee, using a double-blind protocol. Great care was taken to avoid all conflicts of interest.", | |
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| "section": "Preface", | |
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| "text": "ALTA 2017 includes a presentations track, following the workshops since 2015 when it was first introduced. This aims to encourage broader participation and facilitate local socialisation of international results, including work in progress and work submitted or published elsewhere. Presentations were lightly reviewed by the ALTA chairs to gauge overall quality of work and whether it would be of interest to the ALTA community. O ering both archival and presentation tracks allows us to grow the standard of work at ALTA, to better showcase the excellent research being done locally.", | |
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| "text": "ALTA 2017 continues the tradition of including a shared task, this year on correcting OCR errors. Participation is summarised in an overview paper by organisers Diego Moll\u00e1-Alliod and Steve Cassidy. Participants were invited to submit a system description paper, which are included in this volume without review.", | |
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| "section": "Preface", | |
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| "text": "We would like to thank, in no particular order: all of the authors who submitted papers; the programme committee for the time and e ort the put into maintaining the high standards of our reviewing process; the co-chair Stephen Wan for coordinating the logistics that go into running the workshop, from arranging the space, catering, budgets, sponsorship and more; the shared task organisers Diego Moll\u00e1 and Steve Cassidy; our keynote speakers Lewis Mitchell and Robert Dale for agreeing to share their perspectives on the state of the field; and the tutorial presenter Ben Hachey for his e orts towards the three parts of the tutorial. We would like to acknowledge the constant support and advice of the ALTA Executive Committee.", | |
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| "text": "Finally, we gratefully recognise our sponsors: Capital Markets CRC, Sintelix, Google, CSIRO/Data61 and Queensland University of Technology. Importantly, their generous support enabled us to o er travel subsidies to all students presenting at ALTA, and helped to subsidise conference catering costs and student paper awards. ", | |
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| "text": "Lewis Mitchell (Lecturer in Applied Mathematics, University of Adelaide) Abstract. Understanding the nature of influence and information propagation in social networks is of clear societal importance, as they form the basis for phenomena like \"echo chambers\" and \"emotional contagion\". However, these concepts remain surprisingly ill-defined. In studies of large online social networks, proxies for influence and information are routinely employed, leading to confusion as to whether the phenomena they underlie actually exist. In this talk I will demonstrate how online social media streams can be used as proxies for population-level health characteristics such as obesity and happiness, and introduce information-theoretic tools for constructing social networks from underlying information flows between individuals. I will present results relating individual predictability to popularity and contact volume, and introduce a paradigmatic mathematical model of information flow over social networks.Bio. Lewis's research focusses on large-scale methods for extracting useful information from online social networks, and on mathematical techniques for inference and prediction using these data. He works on building tools for real-time estimation of social phenomena such as happiness from written text, and prediction of population-level events like disease outbreaks, elections, and civil unrest.", | |
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| "text": "(Lecturer in Applied Mathematics, University of Adelaide)", | |
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| "section": "Characterising Information and Happiness in Online Social Activity", | |
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| "text": "Abstract. The last few years have seen a tremendous surge in commercial interest in Artificial Intelligence, and with it, a widespread recognition that technologies based on Natural Language Processing can support valuable commercial applications. In this talk, I'll aim to give a comprehensive picture of the commercial NLP landscape, focussing on what I see as the key categories of activity: [1] virtual assistants, including chatbots; [2] text analytics and text mining technologies; [3] machine translation; [4] natural language generation; and [5] text correction technologies. In each case my goal is to sketch the history of work in the area, to identify the major players, and to give a realistic appraisal of the state of the art.Bio. Robert Dale runs the Language Technology Group, an independent consultancy providing unbiased advice to corporations and businesses on the selection and deployment of NLP technologies. Until recently, he was Chief Technology O cer of Arria NLG, where he led the development of a cloud-based natural language generation tool; prior to joining Arria in 2012, he held a chair in the Department of Computing at Macquarie University in Sydney, where he was Director of that university's Centre for Language Technology. After receiving his PhD from the University of Edinburgh in 1989, he taught there for several years before moving to Sydney in 1994. He played a foundational role in building up the NLP community in Australia, and was editor in chief of the Computational Linguistics journal from 2003 to 2012. He writes a semi-regular column titled 'Industry Watch' for the Journal of Natural Language Engineering.", | |
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| "section": "Robert Dale (Principal Consultant, Language Technology Group Pty Ltd)", | |
| "sec_num": null | |
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| "text": "This half-day session will take participants through situations they might face applying Natural Language Processing to real-world problems. We'll choose a canonical task (text classification) and focus on the main issue that faces practitioners in green fields projects -where does the data come from? Our aim is to equip participants with the theoretical background and practical skills to quickly build high-quality text classification models.", | |
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| "section": "Active Learning ... and Beyond! Ben Hachey (The University of Sydney)", | |
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| "text": "Oliver Adams, University of Melbourne \u2022 Timothy Baldwin, University of Melbourne \u2022 Benjamin Borschinger, Google \u2022 Julian Brooke, University of Melbourne \u2022 Lawrence Cavedon, RMIT University \u2022 Trevor Cohn, The University of Melbourne \u2022 Nathalie Colineau, DST Australia \u2022 Mark Dras, Macquarie University \u2022 Dominique Estival, Western Sydney University \u2022 Gabriela Ferraro, CSIRO Data61 \u2022 Hamed Hassanzadeh, The Australian e-Health Research Centre \u2022 Nitin Indurkhya, University of New South Wales \u2022 Sarvnaz Karimi, CSIRO Data61 \u2022 Mac Kim, CSIRO Data61 \u2022 Yitong Li, The University of Melbourne \u2022 Teresa Lynn, Dublin City University \u2022 Andrew MacKinlay, IBM Research \u2022 Diego Moll\u00e1-Alliod, Macquarie University", | |
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| "content": "<table><tr><td>\u2022 Anthony Nguyen, The Australian e-Health Research Centre</td></tr><tr><td>\u2022 Bahadorreza Ofoghi, The University of Melbourne</td></tr><tr><td>\u2022 Sylvester Orimaye, East Tennessee State University</td></tr><tr><td>\u2022 C\u00e9cile Paris, CSIRO Data61</td></tr><tr><td>\u2022 Matthias Petri, The University of Melbourne</td></tr><tr><td>\u2022 Lizhen Qu, CSIRO Data61</td></tr><tr><td>\u2022 Will Radford, Red Marker</td></tr><tr><td>\u2022 Abeed Sarker, University of Pennsylvania</td></tr><tr><td>\u2022 Rolf Schwitter, Macquarie University</td></tr><tr><td>\u2022 Ehsan Shareghi, Monash University</td></tr><tr><td>\u2022 Laurianne Sitbon, Queensland University of Technology</td></tr></table>", | |
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