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Mon, 7 Sep 2015 09:29:55 -0500
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Apologies for cross-posting,

Submissions are invited to AI4BigData'16 to be held at AAAI FLAIRS-29 at Key
Largo on 16th May 2016.
For more information, please visit:

As the Web rapidly evolves, Web users are evolving with it. In an era of social
connectedness, people are becoming increasingly enthusiastic about interacting,
sharing, and collaborating through social networks, online communities, blogs,
Wikis, and other online collaborative media. In recent years, this collective
intelligence has spread to many different areas, with particular focus on fields
related to everyday life such as commerce, tourism, education, and health,
causing the size of the Social Web to expand exponentially.

The distillation of knowledge from such a large amount of unstructured
information, however, is an extremely difficult task, as the contents of today's
Web are perfectly suitable for human consumption, but remain hardly accessible
to machines. The opportunity to capture the opinions of the general public about
social events, political movements, company strategies, marketing campaigns, and
product preferences has raised growing interest both within the scientific
community, leading to many exciting open challenges, as well as in the business
world, due to the remarkable benefits to be had from marketing and financial
market prediction.

The main aim of AI4BigData is to explore the new frontiers of big data computing
for opinion mining and sentiment analysis through machine learning techniques,
knowledge-based systems, adaptive and transfer learning, in order to more
efficiently retrieve and extract social information from the Web.

The special track aims to provide an international forum for researchers in the
field of big data computing for opinion mining and sentiment analysis to share
information on their latest investigations in social information retrieval and
their applications both in academic research areas and industrial sectors. The
broader context of AI4BigData comprehends AI, information retrieval, natural
language processing, and web mining. Topics of interest include but are not
limited to:
• Machine learning for sentiment mining
• Concept-level sentiment analysis
• Biologically-inspired opinion mining
• Sentiment identification & classification
• Association rule learning for opinion mining
• Time evolving opinion & sentiment analysis
• Multi-modal sentiment analysis
• Multi-domain & cross-domain evaluation
• Knowledge base construction & integration with opinion analysis
• Transfer learning of opinion & sentiment with knowledge bases
• Sentiment topic detection & trend discovery
• Social ranking
• Social network analysis
• Human computation
• Opinion spam detection

The special track also welcomes papers on specific application domains of
knowledge-based systems for big data analysis, e.g., influence networks,
customer experience management, intelligent user interfaces, multimedia
management, computer-mediated human-human communication, enterprise feedback
management, surveillance, and art.

November 16th, 2015: Paper submission deadline
January 18th, 2016: Notification of paper acceptance
February 22nd, 2016: Camera-ready of accepted papers
May 17th, 2016: Special track date

Submitted papers must be original, and not submitted concurrently to a journal
or another conference. Double-blind reviewing will be provided, so submitted
papers must use fake author names and affiliations. Papers must use the latest
AAAI Press template, and must be submitted as PDF through EasyChair. There are
three kinds of submissions: full papers (up to 6 pages), short papers (up to 4
pages), and poster abstracts (up to 250 words). Acceptance as a full paper
entails a 20 minute presentation during a regular session, while short papers
and abstracts will be required to participate in the poster session. Rejected
full papers may still be accepted as short papers or poster abstracts. Selected,
expanded versions of Special Track papers will be published in a follow-on
Special Issue of Springer's Cognitive Computation journal.

• Erik Cambria, Nanyang Technological University (Singapore)
• Viviana Patti, University of Turin (Italy)
• Amir Hussain, University of Stirling (UK)
• Newton Howard, MIT Media Laboratory (USA)

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