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Special Sessions

Special sessions are very small and specialized events to be held during the conference as a set of oral and poster presentations that are highly specialized in some particular theme or consisting of the works of some particular international project. The goal of special sessions (minimum 4 papers; maximum 9) is to provide a focused discussion on innovative topics. All accepted papers will be published in a special section of the conference proceedings book, under an ISBN reference, and on CD-ROM support. All papers presented at the conference venue will be available at the SCITEPRESS Digital Library. SCITEPRESS is a member of CrossRef and every paper is given a DOI (Digital Object Identifier). The proceedings are submitted for indexation by Thomson Reuters Conference Proceedings Citation Index (ISI), INSPEC, DBLP, EI (Elsevier Engineering Village Index) and Scopus.


SPECIAL SESSIONS LIST

INDEED 2018Special Session on INsights DiscovEry from LifElog Data
Chair(s): Luca Piras, Duc-Tien Dang-Nguyen and Michael Alexander Riegler

Special Session on INsights DiscovEry from LifElog Data - INDEED 2018

Paper Submission: November 7, 2017
Authors Notification: November 21, 2017
Camera Ready and Registration: November 29, 2017


Co-chairs

Luca Piras
University of Cagliari
Italy
e-mail
 
Duc-Tien Dang-Nguyen
Dublin City University
Ireland
e-mail
 
Michael Alexander Riegler
University of Oslo
Norway
e-mail
 
Scope

In the recent years, lifelogging is rapidly becoming a mainstream research topic. With the rich data captured over a long period of time, these heterogeneous digital lifelogs will require both advanced methods that can provide an insight of the activities of an individual, and systems capable of managing this huge amount of data. A lot of challenges await the scientific community from both the ethical and technological viewpoints. The aim of this special session is to draw together researchers involved in the development of methods for this new and challenging area. The seeked contributions can be either methodological on learning and data analysis (e.g., active and adaptive learning, hypothesis generation, etc.) or focused on solving real world challenges.


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