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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 digital 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 Web of Science / Conference Proceedings Citation Index, DBLP and EI.


SSTM 2012Special Session on Text Mining
Chair(s): Ana Fred

RDBPM 2012Special Session on Research and Development on Business Process Management
Chair(s): Nuno Pina Gonçalves

SSEO 2012Special Session on Enterprise Ontology
Chair(s): Jan Dietz

DART 2012Special Session on Information Filtering and Retrieval: Novel Distributed Systems and Applications
Chair(s): Cristian Lai, Giovanni Semeraro and Alessandro Giuliani

Special Session on Text Mining - SSTM 2012


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

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.

Special Session on Research and Development on Business Process Management - RDBPM 2012


Nuno Pina Gonçalves
DSI, Superior School of Technology, Polithecnical Institute of Setúbal

Business process management (BPM) is a holistic management approach focused on aligning all aspects of an organization with the wants and needs of clients. 2011 is set to be a year of transformation for most IT departments. BPM and SOA are key to obtain higher levels of coordination across the enterprise and increase efficiency. This special session provides a forum for researchers and practitioners in all aspects of BPM including theory, frameworks, methods, techniques, architectures, systems, and empirical findings, attracting innovative contributions from several disciplines such as Computer Science, Management, Services Computing, and Information Technology Management. The main topics addressed include Business Process Design, Business Process Modeling, Business Analytics and Process Optimization, Business Process Execution and Monitoring. It also aims at discussing practical challenges encountered and solutions adopted.

Special Session on Enterprise Ontology - SSEO 2012


Jan Dietz
Computer Science, Delft University of Technology

The notion of Enterprise Ontology adopted in this special session is the systemic notion. Next to the common notion of conceptual schema of a reference universe of discourse (the data view), it comprises the construction view, the process view, and the operation view on organizations. Enterprise Ontology seeks for understanding the implementation independent essence of an organization. By nature, an organization’s essential model is a reference model for all organizations in the same business. Such essential models are crucial in mastering the complexity of enterprise transformations, and in designing enterprise information systems and enterprise-wide knowledge management systems.
This special session welcomes R&D work that applies Enterprise Ontology in understanding organizations and subsequently help analyzing, (re)designing, (re)engineering it them and keeping them operational.

Special Session on Information Filtering and Retrieval: Novel Distributed Systems and Applications - DART 2012


Cristian Lai
Giovanni Semeraro
Dipartimento di Informatica, University of Bari Aldo Moro
Alessandro Giuliani
Department of Department of Mathematics and Computer Science (DMI), University of Cagliari

Nowadays users are more and more interested in information rather than in mere raw data. The huge amount of accessible data sources is growing rapidly. This calls for novel systems providing effective means of searching and retrieving information with the fundamental goal of making it exploitable by humans and machines.
DART focuses on researching and studying new challenges in distributed information filtering and retrieval. In particular, DART aims to investigate novel systems and tools to distributed scenarios and environments. DART will contribute to discuss and compare suitable novel solutions based on intelligent techniques and applied in real-world applications.
Information Retrieval attempts to address similar filtering and ranking problems for pieces of information such as links, pages, and documents. Information Retrieval systems generally focus on the development of global retrieval techniques, often neglecting individual user needs and preferences.
Information Filtering has drastically changed the way information seekers find what they are searching for. In fact, they effectively prune large information spaces and help users in selecting items that best meet their needs, interests, preferences, and tastes. These systems rely strongly on the use of various machine learning tools and algorithms for learning how to rank items and predict user evaluation.