AAAI 2014 Fall Symposium: Natural Language Access to Big Data (NLA2BD)
November 13–15, 2014.
Westin Arlington Gateway in Arlington, Virginia adjacent to Washington, DC.
Motivation and Scope:
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
• Papers due to: July 04, 2014
• Author notifications: July 11, 2014
• Symposium: November 13-15, 2014