alta

	Mon	Tue	Wed	Thu	Fri
8:30-10:00 10:30-12:00	I1, A1	I1, A1	ALTW	I3, A3	I3,A3
1:30-2:30	Lectures Dale (1) Baeza-Yates (1)	Lectures Knott Baeza-Yates (2)	ALTW	Lectures Dale (2) Baldwin	Lectures Paris Wallis Cassidy/Bird
2:30-4:00 4:30-6:00	I2, A2	I2, A2	ALTW	I4, A4	I4, A4

Approximate string matching:
Ricardo Baeza-Yates, University of Chile

ABSTRACT

Lecture 1:
String searching algorithms We will cover all the main paradigms to search strings with and without mistakes, from classical ones such as Knuth-Morris-Pratt and Boyer-Moore to algorithms based in bit parallelism such as shitf-ot and shift-and. The first part will be conceptual mentioning applications to the Web ana other type of data, while the second part will be more technical.

Lecture 2:

BIO:
Ricardo Baeza-Yates received his Ph.D. in CS from U. of Waterloo, Canada, in 1989. During 1993, he received the Organization of American States award for young researchers in exact sciences. In 1994 obtained the Chilean Engineers Institute award for his research work. In 1997, with two Brazilian colleagues obtained the COMPAQ prize to the best Brazilian CS research article in 1996. In 2002 was the first computer scientist incorporated to the Chilean Academy of Sciences. He is the current president of CLEI (Latin American CS Association) and member of the board of governors of the IEEE-CS. Currently he is professor and chair of the CS department at the University of Chile, as well as director of the Center for Web Research. Among other publications, he is co-author of Modern Information Retrieval (Addison-Wesley, 1999) and the 2nd edition of the Handbook of Algorithms and Data Structures (Addison-Wesley, 1991), and co-editor of Information Retrieval: Algorithms and Data Structures (Prentice-Hall, 1992). His research interests include algorithms and data structures, text retrieval, web mining, and visualization applied to databases. He is member of the ACM, EATCS, IEEE (senior), SCCC and SIAM.
http://www.dcc.uchile.cl/~rbaeza/

Introduction to Discourse Representation Theory
Alistair Knott, University of Otago

ABSTRACT
In this seminar I will provide an introduction to Hans Kamp's Discourse Representation Theory (DRT). DRT has been around for over 20 years now: it originated as a relatively small extension of the predicate calculus, and as a result of the many people who have used DRT in their work since then, it has increased in scope quite considerably. It is now probably the dominant framework for formal treatments of natural language semantics.

I will begin by outlining the motivations for 'classical' DRT, which have their origins in hoary philosophical questions about referring expressions in natural language. I will then informally describe the syntax and semantics of DRT. Then I will discuss some extensions of DRT which are now more or less assimilated into the formalism, in particular treatments of plurality and presupposition. I will conclude by looking at some current uses of DRT in language technology applications.

Reference: Hans Kamp, Josef van Genabith and Uwe Reyle "Discourse Representation Theory: An updated survey". DRAFT of an article to appear in the new edition of the Handbook of Philosophical Logic, available at http://www.ims.uni-stuttgart.de/~hans/hpl-drt.pdf

BIO
http://www.cs.otago.ac.nz/staff/ali.html

top

Text planning in the Large: Discourse Structure
Text Planning in the Small: Referring Expressions
Robert Dale, Macquarie University

ABSTRACT
In this series of two lectures we will look at what is involved in getting a computer to plan the content of a text.

Lecture 1:
Text Planning in the Large: Discourse Structure
We introduce the architecture of natural language generation systems, identifying the key components and the information they use. We focus in on the task of taking a body of content to be expressed and organising this into a coherent discourse, and examine a number of different approaches that have been taken to the structural organisation of text.

Lecture 2:
Text Planning in the Small: Referring Expressions
Natural language generation systems not only need to plan how to organise the body of information they want to express into coherent paragraphs. They also need to reason about the detail within individual sentences, and nowhere is this more evident than in the generation of referring expressions. Here the need is to determine how to refer to entities and sets in the domain of discourse so that the hearer knows what is being talked about.

BIO
Professor Robert Dale is Director of the Centre for Language Technology at Macquarie University in Sydney, where he teaches on various aspects of language technology. After completing his PhD in Computational Linguistics at the University of Edinburgh in 1989, he taught in the Centre for Cognitive Science at Edinburgh, before taking up a position with Microsoft in Sydney in 1994. He was Director of the Microsoft Research Institute at Macquarie University (1996-1999). His research interests include intelligent text processing; natural language generation; spoken language dialog systems; and reference and anaphora. He is author or editor of five books and around 60 papers in various aspects of natural language processing, and is editor of the Journal of Computational Linguistics.
http://www.ics.mq.edu.au/~rdale/

top

Language technologies and HCI:
Cecile Paris, CSIRO

ABSTRACT
Human-Computer Interaction (HCI) is concerned with studying how to best design technology so as to ensure that it will fit naturally into the users' environment and be appropriate for the task at hand, and that the interaction between humans and the machine will be smooth. Language is now often employed as a means of interaction. It is thus important to understand some of the principles and methodologies employed in HCI to help design systems. In this lecture, we will look at some of the techniques employed in HCI, such as task analysis and task centred design. We will also discuss the potential for cross-fertilization between the two disciplines (HCI and Natural Language Processing).

BIO
Cécile Paris is a Principal Research Scientist at CSIRO/ICT Centre, leading the area of research concerned with Delivering Information in Context. She is also an Honorary Associate in the Language Technology Centre at Macquarie University (Division of Information and Communication Sciences), and at the School of Information Technologies at Sydney University. Her main research interests lie in the areas of Language Technology, User Modelling and HCI. Cécile did her PhD in Computational Linguistics at Columbia University (New York). She worked 7 years at USC/ISI (Marina del Rey, Los Angeles) after her PhD, leading a research programme in text planning and generation. Before coming to Australia, she was at ITRI (Brighton, UK), leading work on multilingual generation systems. Cécile is currently the chair of CHISIG, the Computer Human Interaction Special Interest Group of the Ergonomics Society of Australia.
http://www.cmis.csiro.au/Cecile.Paris/

top

Linguistic annotation and the Annotation Graph Toolkit
Steven Bird, University of Melbourne

ABSTRACT
Annotated corpora have been a critical component of research in the speech and language sciences for some years. Today, these corpora are being created and deployed for a rapidly expanding set of languages, disciplines and technologies. A wealth of formats and tools have sprung up around this enterprise, many of which are documented on the Linguistic Annotation page [http://www.ldc.upenn.edu/annotation/]. Linguistic annotation is a term which covers any descriptive or analytic notations applied to raw language data. The basic data may be in the form of time functions - audio, video and/or physiological recordings - or it may be textual. The added notations may include transcriptions of all sorts (from phonetic features to discourse structures), part-of-speech and sense tagging, syntactic analysis, "named entity" identification, co-reference annotation, and so on. This lecture will present a model of linguistic annotation which provides a simple framework for representing and manipulating complex, heterogeneous, multi-layered annotations. The model uses "annotation graphs": directed acyclic graphs having labels on the edges and time-offsets on the nodes. The lecture will cover the formalism, the software infrastructure, and practical applications.

BIO
Steven Bird is Associate Professor of Computer Science and Software Engineering, and he teaches human language technology and supervises several research students working in this area. His research focuses on formal and computational models for linguistic information, with application to human language technologies and to the description of the world's ~7,000 languages. Before coming to Melbourne University he did doctoral and post-doctoral research at the University of Edinburgh (1987-94). From 1995-97 he conducted linguistic fieldwork on the languages of western Cameroon, published a dictionary, and helped develop several new writing systems. From 1998-2002 he was associate director of the Linguistic Data Consortium at the University of Pennsylvania, where he led an R&D team working on open-source software for linguistic annotation.
http://www.cs.mu.oz.au/~sb/

top

Linguistic Annotation and the Emu Speech Database System
Steve Cassidy, Macquarie University

ABSTRACT

BIO
http://www.ics.mq.edu.au/~cassidy/

top

Language in a Social Setting: an agent based perspective on Language Technology
Peter Wallis, University of Melbourne

ABSTRACT
As described by Lochbaum, Grosz and Sidner, approaches to computer generated conversation fall into one of two broad categories: the intentional model, in which dialogue structure is analysed from the perspective of user goals, and the more conventional informational model, in which the purpose of language is to convey information. This presentation starts with arguments for taking the intentional perspective and goes on to show how it is applied to developing descriptions of dialogue structure that explicitly address factors commonly grouped under the banner of social intelligence. The motivation for the work described has been the so called agent based approach to AI in which the focus is on the situated and autonomous nature of some software entities. Rather than focusing on what was said, the focus should be on what to say next in order to achieve goals. This line of investigation has highlighted the need for conversational computers to understand social conventions. What is the effect on a human if the machine follows or breaks these conversational norms? The talk is intended for both practitioners currently working with applied language technology such as chat bots or automated call handling, and for graduate students looking for potential research topics in what is traditionally called conversation analysis.

BIO
Peter Wallis has a bachelor of arts from Flinders University with majors in Computer Science and Philosophy, and a Ph.D. from RMIT in semantics for search engines. He has a long history of working on applied natural language: In his Ph.D. work, he used the Longman's Dictionary of Contemporary English (LDOCE) to produce canonical versions of text meaning. He then worked at Defence Science and Technology Organization on information extraction, and initiated the "fact extractor" architecture that has gone operational at several sites within Defence. Since 1998 he has been developing an interest in dialogue and is currently trying to commercialize some ideas on dialogue management for the VoiceXML community. Key publications have been on the evaluation of Language Technology, and when pressed he will argue for a functional view of semantics. http://www.cs.mu.oz.au/~peter/

top

Deep Lexical Acquisition
Timothy Baldwin, CSLI Stanford

ABSTRACT
ABSTRACT: Deep processing involves applying "precision grammars" (i.e. linguistically-precise grammars, such as HPSGs) to natural language analysis, and has significant advantages over shallow methods in terms of its ability to capture fine-grained lexical and constructional interactions and produce a rich semantic representation. The main limitation of deep processing is coverage, which tends to be restricted due to the detailed annotation required to encode individual lexical items in precision grammars. This talk will tackle the question of how to expand the coverage of a precision grammar through the automatic acquisition of lexical features and ultimate type classification of a given word. I will use the English Resource Grammar as a test case, and outline a range of methods by which new lexical items can be acquired either directly through the application of the grammar, or indirectly through techniques drawing on corpus data and/or semantic ontologies.

BIO
Timothy Baldwin is a Senior Researcher at the Centre for the Study of Language and Information (CSLI), Stanford University. He is a member of the CSLI LinGO Multiword Expression Project, specialising in the lexical acquisition, semantic classification and machine translation of multiword expressions. Other recent research interests include computational lexical semantics, the interface between theoretical and computational linguistics, and computer-assisted language learning applications for computational linguistics. http://www-csli.stanford.edu/~tbaldwin/

top

Convenor
A/Prof Steven Bird
Dept of Computer Science
University of Melbourne

Local Arrangements
Cathy Bow
Dept of Computer Science
University of Melbourne

Conference Management
The University of Melbourne
Jen Westphal
Telephone: +61 (03) 8344 6107
Facsimile: +61 (03) 8344 6122
Email: westphal@unimelb.edu.au

Bronwen Hewitt
Telephone: +61 (03) 8344 6389
Facsimile: +61 (03) 8344 6122
Email: bhewitt@unimelb.edu.au

top