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AAAI 2014 FALL SYMPOSIUM: NATURAL LANGUAGE ACCESS TO BIG DATA <br>
November 13–15, 2014 Westin Arlington Gateway in Arlington, Virginia
adjacent to Washington, DC<br>
<br>
<a class="moz-txt-link-freetext"
href="https://sites.google.com/site/nlabd2014/home">https://sites.google.com/site/nlabd2014/home</a><br>
<br>
Important Dates:<br>
<br>
<b>• Papers due to: July 6, 2014</b><b><br>
</b><b><br>
</b><b>• Author notifications: July 31, 2014</b><b><br>
</b><b><br>
</b><b>• Accepted camera-ready copy due to AAAI: September 10, 2014</b><b><br>
</b><b><br>
</b><b>• Symposium: November 13–15, 2014</b><br>
<br>
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. <br>
<br>
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.<br>
<br>
Call for Papers:<br>
<br>
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:<br>
<br>
• Natural language interaction technologies (e.g., in the context of
knowledge navigation; personal assistant)<br>
• Speech interfaces and interactive question answering<br>
• Automatic question answering based on structured data sources<br>
• Natural language access to the Semantic Web <br>
• Question answering and natural language interfaces to Linked Data<br>
• Formalization of structured information / queries (RDF, OWL,
SPARQL)<br>
• Machine learning techniques (e.g., large-scale hierarchical
classification) for translating the users' information needs into
formal queries <br>
• Information extraction at web scale that supports natural language
access <br>
• Web mining and social network analysis<br>
• Social media analysis and opinion mining<br>
• Text summarization (e.g., question-focused summarization)<br>
• Natural language processing for document analysis including
information extraction, semantic role labeling and co-reference
resolution<br>
• Architectures for natural language access to big data<br>
• UIMA modules<br>
• Applications and projects<br>
<br>
Programm Committee: <br>
<br>
• Gerhard Weikum<br>
Max-Planck-Institut für Informatik, Saarbrücken, Germany<br>
<br>
• Philipp Cimiano<br>
Bielefeld University - CITEC, Germany<br>
<br>
• Zornitsa Kozareva<br>
Yahoo Research, Silicon Valley, USA<br>
<br>
• Chris Biemann<br>
TU Darmstadt, Germany <br>
<br>
• Florian Röhrbein<br>
Technische Universität München, Germany<br>
<br>
• Saurav Sahay<br>
Intel Labs - Experience Technology, Santa Clara, CA, USA <br>
<br>
• Mohamed Yahya<br>
Max-Planck-Institut für Informatik, Saarbrücken, Germany<br>
<br>
• Maximilian Viermetz<br>
Siemens AG - Corporate Technology, Germany<br>
<br>
• James Fan<br>
IBM T. J. Watson Research Center, NY, USA<br>
<br>
• Ken Barker<br>
IBM T. J. Watson Research Center, NY, USA<br>
<br>
• Günter Neumann <br>
German Research Center for AI, Saarbrücken, Germany<br>
<br>
• Martin Theobald<br>
University of Antwerp, Belgium<br>
<br>
• Paul Buitelaar <br>
Digital Enterprise Research Institute, Ireland <br>
<br>
• Jochen Leidner <br>
Thomson Reuters, United Kingdom<br>
<br>
• Lora Aroyo <br>
VU University Amsterdam, The Netherlands <br>
<br>
Organizing Committee: <br>
<br>
Dan G. Tecuci <br>
IBM Watson<br>
Austin, TX<br>
Email: <a class="moz-txt-link-abbreviated"
href="mailto:dan.tecuci@gmail.com">dan.tecuci@gmail.com</a><br>
<a class="moz-txt-link-freetext" href="http://www.dantecuci.com">http://www.dantecuci.com</a><br>
<br>
Ulli Waltinger<br>
Siemens AG / Corporate Technology <br>
Research & Technology Center<br>
Business Analytics & Monitoring <br>
Knowledge Modeling & Retrieval (CT RTC BAM KMR) <br>
Otto-Hahn-Ring 6<br>
81739 München, Deutschland<br>
Email: <a class="moz-txt-link-abbreviated"
href="mailto:ulli.waltinger@siemens.com">ulli.waltinger@siemens.com</a><br>
<br>
Daniel Sonntag<br>
German Research Center for Artificial Intelligence<br>
Intelligent User Interfaces<br>
Stuhlsatzenhausweg 3<br>
66123 Saarbruecken, Germany<br>
Email: <a class="moz-txt-link-abbreviated"
href="mailto:daniel.sonntag@dfki.de">daniel.sonntag@dfki.de</a><br>
<a class="moz-txt-link-freetext"
href="http://www.dfki.de/%7Esonntag/">http://www.dfki.de/~sonntag/</a><br>
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