Workshop on Adaptive Natural Language Processing at IJCAI 2015

SKATER members organized the Workshop on Adaptive Natural Language Processing

in conjunction with IJCAI 2015

in Buenos Aires, Argentina, July 25-27 2015

 

Motivation and Aims

Natural Language Processing is becoming more and more ubiquitous as technologies become omnipresent in our daily life. This involves a huge effort to develop language-based interfaces, text analytics, search engines, writing assitants among other systems and their related tools and resources. Adaptation has been key to facilitate rapid development of language-based systems, with reuse of existing resources as alternatives to creating tools and resources from scratch. These approaches have benefited from the recent surge of complex Machine Learning approaches as applied to NLP tasks. This is the case for Semi-supervised and Unsupervised Learning, Active Learning, Domain Adaptation, and even Representation Learning and Deep Learning, which have had a very positive impact on NLP tasks and applications.

This workshop aims to provide a meeting point for researchers working on the portability of language resources and methodologies across languages and domains, with a special focus on exploiting available knowledge as a base to facilitate and enhance new developments. We understand that there is a common factor between tasks like porting a parser between related languages, adapting a dialogue system for a different domain, using rules inferred from an annotated corpus together with an unannotated corpus to port an information extraction system to another domain, or simplifying texts for different kinds of readers, among others. We believe that sharing insights on such approaches will be enriching and will contribute to a better understanding of the problems and solutions.

We expect that themes like Representation Learning, Deep Learning and Active Learning, and their successful applications to various areas of NLP, will raise interesting, intellectually challenging discussions.


Workshop Topics

Contributions may present results from completed as well as ongoing research, with an emphasis on novel approaches, methods, ideas, and perspectives.

The topics of the workshop include, but are not limited to:

Semi-supervised learning, Deep Learning, Active learning and Representation learning for domain adaptation, language portability and task portability
Adaptation and reuse of tools and resources for closely related languages
Adaptation of highly valuable resources, like treebanks, to languages not closely related
Linguistic issues in language portability: false friends, asymmetric discretization of semantic continuum
Learning from multiple domains
Development of multi-domain datasets
Evaluation paradigms for complex learning
Domain adaptation for specific applications: parsing, machine translation, information extraction, document classification, sentiment analysis and author attribution and profiling

Format of submissions

Submissions are invited for papers presenting high quality, previously unpublished research. Selection criteria include originality of ideas, correctness, clarity and significance of results and quality of presentation.

We welcome two types of contributions:

Long papers (10 pages), presenting substantial, original and completed research work. Accepted long papers will be presented orally.
Short papers (6 pages), with a small, focused contribution, work in progress, a negative result or an opinion piece. Accepted short papers will be presented either orally or as a poster.

Short papers can be combined with a system demonstration.

The only accepted format for submitting papers is Adobe PDF. Papers should follow IJCAI-15 formatting Guidelines.

As the review process will be double-blind, your submission must not include the author(s) name(s) and affiliation(s). Furthermore, self-references that reveal the author's identity, e.g., "We previously showed (Pérez, 2003) ...", must be avoided. Instead, citations such as "Pérez (2003) previously showed ...", must be used.

Submissions will be electronic, the submission site will be made available soon.


Important Dates

Submission deadline: April 27 2015
Acceptance/rejection notification: May 20 2015
Camera-ready deadline: May 30, 2015
Workshop: July 25-27 2015 at IJCAI 2015


Programme Committee

Luciana Benotti (UNC, Argentina)
Xavier Carreras (XEROX-XRCE, France)
Helena Caseli (UFSCar, Brazil)
José Castaño (UBA, Argentina)
Carlos Iván Chesñevar (UNS, Argentina)
Martín Domínguez (UNC, Argentina)
Pablo Duboue (Les Laboratoires Foulab, Canada)
Marcelo Errecalde (UNSL, Argentina)
Hugo Jair Escalante (INAOE, Mexico)
Paula Estrella (UNC, Argentina)
Mikel Forcada (UA, Spain)
Maria Fuentes Fort (UPC, Spain)
Xavier Gómez Guinovart (UVigo, Spain)
Agustín Gravano (UBA, Argentina)
Franco Luque (UNC, Argentina)
Rada Mihalcea (UNT, USA)
Maria das Graças Volpe Nunes (USP, Brazil)
Lluís Padró (UPC, Spain)
Muntsa Padró (Nuance, Canada)
Martí Quixal (UTübingen, Germany)
Thiago Pardo (USP, Brazil)
Ted Pedersen (UMN, USA)
German Rigau (UPV, Spain)
Aiala Rosá (UdelaR, Uruguay)
Paolo Rosso (UV, Spain)
Horacio Saggion (UPF, Spain)
Thamar Solorio (UH, USA)
Juan-Manuel Torres-Moreno (LIA/UAPV, France)
Cristina Vertan (UH, Germany)
Dina Wonsever (UdelaR, Uruguay)

Organizing Committee

Laura Alonso i Alemany (UNC, Argentina)
Núria Bel (UPF, Spain)
Irene Castellón (UB, Spain)
Manuel Montes y Gómez (INAOE, Mexico)

 

The Massive Open On-line Course on Machine Translation that will start on October 23

The course entitled: "Approaches to Machine Translation: rule-based, statistical and hybrid" is an opportunity to learn about the theory behind MT algorithms; how major on-line MT systems work; and how to manage open-source software to reproduce prototypes of such systems under a do-it-yourself basis.

The MOOC is offered by the UPC under the CANVAS platform. Students that successfully pass tests and assignments will be granted a certificate by the same University.

22/09/2014 - Prof. David Zhang - Biometrics Computing

Title Biometrics Computing
Speaker Prof. David Zhang, Hong Kong Polytechnic University
Room Aula Seminaris D5-007, Campus Nord UPC
Date 22/09/2014
Time 10:00h
Abstract

In recent times, an increasing, worldwide effort has been devoted to the development of automatic personal identification systems that can be effective in a wide variety of security contexts. As one of the most powerful and reliable means of personal authentication, biometrics has been an area of particular interest. It has led to the extensive study of biometric technologies and the development of numerous algorithms, applications, and systems, which could be defined as Biometrics Computing.  This presentation will systematically explain this new research trend. As case studies, a new biometrics technology (palmprint recognition) and two new biometrics applications (medical biometrics and aesthetical biometrics) are introduced. Some useful achievements could be given to illustrate their effectiveness.

Short CV:
David Zhang graduated in Computer Science from Peking University. He received his MSc in 1982 and his PhD in 1985 in Computer Science from the Harbin Institute of Technology (HIT), respectively. From 1986 to 1988 he was a Postdoctoral Fellow at Tsinghua University and then an Associate Professor at the Academia Sinica, Beijing. In 1994 he received his second PhD in Electrical and Computer Engineering from the University of Waterloo, Ontario, Canada. He is  a Chair Professor since 2005 at the Hong Kong Polytechnic University where he is the Founding Director of the Biometrics Research Centre (UGC/CRC) supported by the Hong Kong SAR Government in 1998. He also serves as Visiting Chair Professor in Tsinghua University, and Adjunct Professor in Peking University, Shanghai Jiao Tong University, HIT, and the University of Waterloo. He is the Founder and Editor-in-Chief, International Journal of Image and Graphics (IJIG); Book Editor, Springer International Series on Biometrics (KISB); Organizer, the International Conference on Biometrics Authentication (ICBA); Associate Editor of more than ten international journals including IEEE Transactions and so on; and the author of more than 10 books,over 300 international journal papers and around 30 patents from USA/Japan/HK/China. Recently, he has selected as a Highly Cited Researcher 2014 by Thomson Reuters (Total 3,215 in 21 fields of the sciences & social sciences, each ranking among the top 1% most cited during over past 11 years). Professor Zhang is a Croucher Senior Research Fellow, Distinguished Speaker of the IEEE Computer Society, and a Fellow of both IEEE and IAPR.

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