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EAST - FLAIRS 2017 : lEArning from heterogeneouS data analyTics - FLAIRS

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Link: http://www.textmining.biz/Conf/EAST2017
 
When May 22, 2017 - May 24, 2017
Where Marco Island, Florida, USA
Submission Deadline Nov 21, 2016
Notification Due Jan 23, 2017
Final Version Due Feb 27, 2017
Categories    big data   data mining   information retrieval   text-mining
 

Call For Papers

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The 30th International FLAIRS Conference

Special track:
EAST: lEArning from heterogeneouS data analyTics

http://www.textmining.biz/Conf/EAST2017

May 22-24, 2017
The Hilton Marco Island Beach Resort and Spa
Marco Island, Florida, USA

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AIMS AND TOPICS

Recent technological advancements have led to a deluge of data from distinctive domains (e.g., health care and scientific sensors, user-generated data, Internet and financial companies, and supply chain systems) over the past decades. Data Analytics examines such large amounts of data to uncover hidden patterns, correlations and other insights.
Data comes in different forms: (i) Structured data (i.e. data in traditional databases relatively easy to manage, store, query, and analyze), (ii) Unstructured data like documents. In order to manage the heterogeneity, different kinds of features associated with data have to be extracted and exploited (e.g. numerical, qualitative, textual, graphs, etc.). Approaches to analyze such mixed data include pre processing, data preparation, post processing, data mining, data visualization, and so forth.
In this context, the EAST track focuses on the study of variety/heterogeneity of data, one of the 3V of Big Data (volume, variety, and velocity). And more precisely, the track addresses the development of new approaches dedicated to this crucial issue.

Heterogeneity may appear in two different forms:
- Semantic: heterogeneous fields, heterogeneous data content, heterogeneous semantic sources (i.e. thesaurus), etc.
- Syntactic: heterogeneous texts (structured/unstructured, standard/non-standard languages, etc.), heterogeneous images and video, etc.

The thematic track EAST is devoted to compiling the state-of-the-art in managing heterogeneity for data analytics, from integration to visualization. It will highlight the recent advances in this research field. Particularly welcome are reports, research, position and application papers (medicine, biology, environment, agriculture, chemistry, financial, law, and so on), issued either from the academic or industrial worlds.


SUBMISSION

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 Word template or LaTeX macro package, and must be submitted as PDF through the EasyChair conference system.

There are three kinds of submissions:
- full paper - a paper of high quality, which will be published in the proceedings (up to 6 pages) and will be presented by the author in a corresponding track (20 minute oral presentation)
- short paper - a paper that shows some novelty and general interest, but is more preliminary or in the early stages of development, which also get published in the proceedings (up to 4 pages) and the author presents the work in a poster session
- poster abstract, which will be published as abstract only (up to 250 words) and the author presents the work in a poster session.

See more details: https://sites.google.com/site/flairs30conference/call-for-papers

Submission web site (EasyChair): https://easychair.org/conferences/?conf=flairs30
[Select "Machine Learning for Heterogeneous Data" track]


IMPORTANT DATES

November 21, 2016: Paper submission deadline
January 23, 2017: Paper acceptance notification
February 6, 2017: Poster abstract submission
February 13, 2017: Poster abstract notification
February 27, 2017: Camera ready version due (AAAI publication)
May 22-24, 2017: Conference


CHAIRS

Juan Antonio Lossio-Ventura, University of Florida, USA
Mathieu Roche, Cirad, TETIS, France
Maguelonne Teisseire, Irstea, TETIS, France

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