LINGUIST List 23.633|
Tue Feb 07 2012
Calls: Computational Ling, Discourse Analysis/South Korea
Editor for this issue: Alison Zaharee
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1. Agnes Sandor ,
Detecting Structure in Scholarly Discourse
Message 1: Detecting Structure in Scholarly Discourse
From: Agnes Sandor <agnes.sandorxrce.xerox.com>
Subject: Detecting Structure in Scholarly Discourse
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Full Title: Detecting Structure in Scholarly Discourse
Short Title: DSSD2012
Date: 12-Jul-2012 - 12-Jul-2012
Location: Jeju Island, Korea, South
Contact Person: Anita de Waard
Meeting Email: < click here to access email >
Web Site: http://www.nactem.ac.uk/dssd/index.php
Linguistic Field(s): Computational Linguistics; Discourse Analysis
Call Deadline: 11-Mar-2012
ACL 2012 Workshop on Detecting Structure in Scholarly Discourse, DSSD2012
July 12, 2012
International Convention Center Jeju
Jeju Island, Republic of Korea
The detection of discourse structure in scientific documents is important for a number of tasks, including biocuration efforts, text summarization, error correction, information extraction and the creation of enriched formats for scientific publishing. Currently, many parallel efforts exist to detect a range of discourse elements at different levels of granularity and for different purposes. Discourse elements detected include the statement of facts, claims and hypotheses, the identification of methods and protocols, and as the differentiation between new and existing work. In medical texts, efforts are underway to automatically identify prescription and treatment guidelines, patient characteristics, and to annotate research data. Ambitious long-term goals include the modeling of argumentation and rhetorical structure and more recently narrative structure, by recognizing 'motifs' inspired by folktale analysis.
A rich variety of feature classes is used to identify discourse elements, including verb tense/mood/voice, semantic verb class, speculative language or negation, various classes of stance markers, text-structural components, or the location of references. These features are motivated by linguistic inquiry into the detection of subjectivity, opinion, entailment, inference, but also author stance and author disagreement, motif and focus.
The goal of the 2012 workshop 'Detecting Structure in Scholarly Discourse' is to discuss and compare the techniques and principles applied in these various approaches, to consider ways in which they can complement each other, and to initiate collaborations to develop standards for annotating appropriate levels of discourse, with enhanced accuracy and usefulness.
2nd Call for Papers:
We are inviting submissions of long papers describing original research work that span the range from theory to application, including research on and the practice of manual and automated annotation systems, and discuss questions like the following:
- What correlations can be demonstrated among document structure, argumentation and rhetorical functions?
- What are the text's linguistic and philosophical motivations underpinning current efforts to identify discourse structure? Are the assumptions made by current text processing tools supported by discourse linguistic research; are there unused opportunities for fruitful cross-fertilization?
- Can we port parallel efforts from neighboring fields, such as motifs in folktale research, to annotate and detect narrative structures?
- Which discourse annotation schemes are the most portable? Can they be applied to both full papers and abstracts? Can they be applied to texts in different domains and different genres (research papers, reviews, patents, etc)?
- How can we compare annotations, and how can we decide which features, approaches or techniques work best? What are the most topical use cases? How can we evaluate performance and what are the most appropriate tasks?
- What corpora are currently available for comparing and contrasting discourse annotation, and how can we improve and increase these?
- How applicable are discourse annotation efforts for improving methods of publishing, detecting and correcting authors' errors at the discourse level, or summarizing scholarly text? How close are we to implementing them at a production scale?
March 11, 2012: Submission deadline
April 15, 2012: Notification of acceptance
April 30, 2012: Camera-ready paper
July 12, 2012: Workshop
Please use ACL style files listed in:
Authors are requested to submit their abstracts at:
The accepted papers will be published in the DSSD2012 Workshop Proceedings.
Sophia Ananiadou, National Centre for Text Mining and University of Manchester
Antal van den Bosch, Radboud University Nijmegen
Ágnes Sándor, Xerox Research Europe, Grenoble
Hagit Shatkay, University of Delaware
Anita de Waard, Elsevier Labs/Utrecht University
Catherine Blake, University of Illinois at Urbana-Champaign, USA
Kevin Cohen, University of Colorado, School of Medicine, USA
Nigel Collier, National Institute of Informatics, Japan
Walter Daelemans, University of Antwerp, Belgium
Robert Dale, Macquarie University, Australia
Kjersti Fløttum, University of Bergen, Norway
Rocana Girju, University of Illinois at Urbana-Champaign, USA
Lynette Hirschman, MITRE, USA
Halil Kilicoglu, Concordia University, Canada
Jin-Dong Kim, The University Of Tokyo, Japan
Anna Korhonen, Cambridge University, UK
Maria Liakata, Aberystwyth University, UK
Roser Morante, University of Antwerp, Belgium
Raheel Nawaz, University of Manchester, UK
Dragomir Radev, University of Michigan, USA
Dietrich Rebholz-Schuhmann, EBI, UK
Andrey Rzhetsky, University of Chicago, USA
Caroline Sporleder, Saarland University, Germany
Padmini Srinivasan, University of Iowa, USA
Simone Teufel, University of Cambridge, UK
Paul Thompson, University of Manchester, UK
Jun'ichi Tsujii, Microsoft Research Asia, China
Lucy Vanderwende, Microsoft Research, USA
Anita de Waard, Disruptive Technology Director, Elsevier Labs
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