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Special Session
Special Session on
Text Mining
 - SSTM 2013

19 - 22 September, 2013 - Vilamoura, Algarve, Portugal

Within the International Conference on Knowledge Discovery and Information Retrieval - KDIR 2013


CHAIR

Ana Fred
Instituto de Telecomunicações and Instituto Superior Técnico (University of Lisbon)
Portugal

 
Brief Bio
Ana Fred received the M.S. and Ph.D. degrees in Electrical and Computer Engineering, in 1989 and 1994, respectively, both from Instituto Superior Técnico (IST), Technical University of Lisbon, Portugal. She is a Faculty Member of IST since 1986, where she has been a professor with the Department of Electrical and Computer Engineering, and more recently with the Department of Biomedical Engineering. She is a researcher at the Pattern and Image Analysis Group of the Instituto de Telecomunicações. Her main research areas are on pattern recognition, both structural and statistical approaches, with application to data mining, learning systems, behavioral biometrics, and biomedical applications. She has done pioneering work on clustering, namely on cluster ensemble approaches. Recent work on biosensors hardware (including BITalino – and ECG-based biometrics (Vitalidi project) have been object of several nacional and internacional awards, as well as wide dissemination on international media, constituting a success story of knowledge transfer from research to market. She has published over 160 papers in international refereed conferences, peer reviewed journals, and book chapters.

SCOPE

With the increasing popularity and availability of Internet-based technologies, as well as the proliferation of digital computing devices and their use in communication, huge amounts of Human generated content is produced every day in the form of documents, email, instant messaging, social network sites, blogs, and other textual corpora. As a result, we have witnessed an increased demand for systems and algorithms capable of mining textual data, seeking interesting characteristics, hidden patterns, structure, trends, knowledge and key relationships within these large textual corpora. Text mining, combining the disciplines of data mining, information extraction, information retrieval, text categorization, probabilistic modeling, linear algebra, machine learning, and computational linguistics, is a new interdisciplinary field that emerged to address these issues. Examples of emergent applications include metadata generation, visualization techniques, information extraction, text segmentation and classification, text summarization, and trend analysis, to name a few.
This special session aims at sharing new ideas and works on models and approaches for improving over state of the art techniques for mining unstructured, semi-structured, and fully structured textual data.

IMPORTANT DATES

Paper Submission: July 3, 2013 (expired)
Authors Notification: July 16, 2013 (expired)
Camera Ready and Registration: July 30, 2013 (expired)

PROGRAM COMMITTEE MEMBERS

Fernando Batista, DCTI, ISCTE-IUL & INESC-ID, Portugal
Bruno Martins, Departamento de Engenharia Informática,, Portugal

PAPER SUBMISSION

Prospective authors are invited to submit papers in any of the topics listed above.
Instructions for preparing the manuscript (in Word and Latex formats) are available at: Paper Templates
Please also check the Guidelines and Templates.
Papers should be submitted electronically via the web-based submission system at: http://www.insticc.org/Primoris

PUBLICATIONS

All accepted papers will be published in a special section of the conference proceedings book - under an ISBN reference and on CD-ROM support - and submitted for indexation by Thomson Reuters Conference Proceedings Citation Index (ISI), INSPEC, DBLP, EI (Elsevier Index) and Scopus.
SCITEPRESS is member of CrossRef (http://www.crossref.org/).
All papers presented at the conference venue will be available at the SCITEPRESS Digital Library

SECRETARIAT CONTACTS

KDIR Special Sessions - SSTM 2013
e-mail: kdir.secretariat@insticc.org
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