[Corpora-List] AAAI 2014 Fall Symposium: Natural language access to big data (extended deadline July 6)

[Daniel Sonntag]

AAAI 2014 FALL SYMPOSIUM: NATURAL LANGUAGE ACCESS TO BIG DATA
November 13--15, 2014 Westin Arlington Gateway in Arlington, Virginia 
adjacent to Washington, DC

https://sites.google.com/site/nlabd2014/home

Important Dates:

*. Papers due to: July 6, 2014**
**
**. Author notifications: July 31, 2014**
**
**. Accepted camera-ready copy due to AAAI: September 10, 2014**
**
**. Symposium: November 13--15, 2014*

Today's enterprises need to make decisions based on analyzing massive 
and heterogeneous data sources. More and more aspects of decision making 
are driven by data, and as a result, more and more business users need 
access to data. Offering easy access to the right data to diverse 
business users is of growing importance. There are several challenges 
that must be overcome to meet this goal. One is the sheer volume: 
enterprise data are predicted to grow by 800 percent in the next five 
years. The biggest part (80 percent) are stored in unstructured 
documents, most of which are lacking informative meta data or semantic 
tags (beyond date, size, and author) that might help in accessing them. 
A third challenge comes from the need to offer access to these data for 
different types of users, most of whom are not familiar with the 
underlying syntax or semantics of the data.

Natural Language Interfaces and Question Answering Systems, such as 
Watson, Smartweb, Siri, Start, or Evi, have been successfully 
implemented in various domains; for example in encyclopedic knowledge 
bases (e.g., IBM`s Jeopardy Challenge), in the field of energy (e.g., 
DGRC), or in the domain of mathematics (e.g., Wolfram Alpha). Following 
up on prior work in natural language interfaces to databases (NLIDB) and 
question answering (QA) systems, this workshop brings together experts 
from both academia and industry to present their most recent work 
related to problems that leverage natural language in the context of big 
data. They can share information on their latest investigations and 
exchange ideas and thoughts in order to push the research frontier 
towards new technologies that tackle the aspect of natural language 
access to large-scale and heterogeneous data.

Call for Papers:

We welcome the submission of research papers on all aspects of natural 
language access and question answering to large-scale structured and 
unstructured data. The following topics are of particular interest:

. Natural language interaction technologies (e.g., in the context of 
knowledge navigation; personal assistant)
. Speech interfaces and interactive question answering
. Automatic question answering based on structured data sources
. Natural language access to the Semantic Web
. Question answering and natural language interfaces to Linked Data
. Formalization of structured information / queries (RDF, OWL, SPARQL)
. Machine learning techniques (e.g., large-scale hierarchical 
classification) for translating the users' information needs into formal 
queries
. Information extraction at web scale that supports natural language access
. Web mining and social network analysis
. Social media analysis and opinion mining
. Text summarization (e.g., question-focused summarization)
. Natural language processing for document analysis including 
information extraction, semantic role labeling and co-reference resolution
. Architectures for natural language access to big data
. UIMA modules
. Applications and projects

Programm Committee:

. Gerhard Weikum
   Max-Planck-Institut für Informatik, Saarbrücken, Germany

. Philipp Cimiano
   Bielefeld University - CITEC, Germany

. Zornitsa Kozareva
   Yahoo Research, Silicon Valley, USA

. Chris Biemann
   TU Darmstadt, Germany

. Florian Röhrbein
   Technische Universität München, Germany

. Saurav Sahay
   Intel Labs - Experience Technology, Santa Clara, CA, USA

. Mohamed Yahya
   Max-Planck-Institut für Informatik, Saarbrücken, Germany

. Maximilian Viermetz
   Siemens AG - Corporate Technology, Germany

. James Fan
   IBM T. J. Watson Research Center, NY, USA

. Ken Barker
   IBM T. J. Watson Research Center, NY, USA

. Günter Neumann
   German Research Center for AI, Saarbrücken, Germany

. Martin Theobald
   University of Antwerp, Belgium

. Paul Buitelaar
   Digital Enterprise Research Institute, Ireland

. Jochen Leidner
   Thomson Reuters, United Kingdom

. Lora Aroyo
   VU University Amsterdam, The Netherlands

Organizing Committee:

Dan G. Tecuci
IBM Watson
Austin, TX
Email: dan.tecuci at gmail.com
http://www.dantecuci.com

Ulli Waltinger
Siemens AG / Corporate Technology
Research & Technology Center
Business Analytics & Monitoring
Knowledge Modeling & Retrieval (CT RTC BAM KMR)
Otto-Hahn-Ring 6
81739 München, Deutschland
Email: ulli.waltinger at siemens.com

Daniel Sonntag
German Research Center for Artificial Intelligence
Intelligent User Interfaces
Stuhlsatzenhausweg 3
66123 Saarbruecken, Germany
Email: daniel.sonntag at dfki.de
http://www.dfki.de/~sonntag/
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