Fwd: EXTENDED DEADLINE - Call for Papers: KDBI 2009 - Knowledge Discovery and Business Intelligence
Carlos Soares
csoares at fep.up.pt
Fr Apr 10 13:18:43 CEST 2009
Please, distribute
> Carlos
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>
> Begin forwarded message:
>
>> From: "Nuno C. Marques" <nmm at di.fct.unl.pt>
>> Date: 10 de abril de 2009 10:35:15 GMT+01:00
>> To: Joaquim Silva <jfs at di.fct.unl.pt>, ning chen <ningchen74 at gmail.com
>> >, vlobo at netcabo.pt, Carlos Soares <csoares at fep.up.pt>, Alípio Má
>> rio Jorge <amjorge at fep.up.pt>, Pascal Hitzler <hitzler at aifb.uni-karlsruhe.de
>> >
>> Subject: EXTENDED DEADLINE - Call for Papers: KDBI 2009 - Knowledge
>> Discovery and Business Intelligence
>>
>
>> Dear KDBI Program Committee member,
>>
>> Please distribute the announce for the extended deadline of the
>> KDBI 2009-Knowledge Discovery and Business Intelligence call for
>> papers (sorry for any duplicate messages).
>>
>> Best regards,
>> Nuno C. Marques
>>
>>
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>> 2nd Call for Papers: KDBI 2009-Knowledge Discovery and Business
>> Intelligence
>> a thematic track of EPIA 2009, the 14th Portuguese Conference on
>> Artificial Intelligence
>> Aveiro, Portugal, October 12-15, 2009
>>
>> http://epia2009.web.ua.pt/kdbi
>>
>>>> EXTENDED DEADLINE for paper submission: April 29, 2009 <<
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>>
>> Knowledge Discovery and Business Intelligence
>>
>> The aim of this thematic track is to gather the latest research in
>> Knowledge Discovery (KD) and Business Intelligence (BI). We
>> encourage papers that deal with the interaction with the end users,
>> taking into account how easily one can understand data model's
>> representation of extracted knowledge or encode expert knowledge,
>> as well as its impact on real organizations. In particular, papers
>> that describe experience and lessons learned from KD/BI projects
>> and/or present business and organizational impacts using AI
>> technologies, are welcome.
>>
>> The amount of data representing the activities of organizations
>> that is stored in databases is exponentially growing. Moreover,
>> business organizations are increasingly moving towards decision-
>> making processes that are based on information. Thus, pressure to
>> extract as much useful information as possible from these data is
>> very strong. Knowledge Discovery (KD) is a branch of the Artificial
>> Intelligence (AI) field that aims to extract useful and
>> understandable high-level knowledge from complex and/or large
>> volumes of data. Business Intelligence (BI) is an umbrella term
>> that represents computer architectures, tools, technologies and
>> methods to enhance managerial decision making in public and
>> corporate enterprises, from operational to strategic level.
>>
>> KD and Data Mining (DM) are faced with new challenges. The temporal
>> and spatial nature of the data generation demands new learning
>> approaches, since samples' observations are no longer independent
>> and the underlying regularities may change over time. New
>> challenges are also to be considered when integrating background
>> knowledge into the learning processes. Indeed, the success of
>> hybrid models for knowledge understanding and the dead-end of
>> several purely experimental methods in machine learning and DM are
>> pointing to a more rationalistic view. In this context, the
>> understanding of data and human mind emerges as crucial in
>> combining KD with Cognitive Models. Namely, results in inductive
>> logic or in neuro-symbolic methods seem to show the need of more
>> knowledge aware models. Moreover, AI plays a crucial role in BI,
>> providing methodologies to deal with prediction, optimization and
>> adaptability to dynamic environments, in an attempt to offer
>> support to better (more informed) decisions. In effect, several AI
>> techniques can be used to address these problems, namely KD/DM,
>> Evolutionary Computation and Modern Optimization, Forecasting,
>> Neural Computing and Intelligent Agents.
>>
>> Topics of Interest
>>
>> * Data Analysis, including Knowledge Discovery, Data Mining,
>> Machine Learning and Statistical Methods
>> * Logic and Philosophy of Scientific Discovery and its relevance
>> to Knowledge Discovery and Business Intelligence
>> * Hybrid Learning Models and Methods
>> * Domain Knowledge Discovery (e.g. Learning from Heterogeneous,
>> Unstructured and Multimedia data, Networks, Graphs and Link Analysis)
>> * Cognitive Models including Human-machine interaction for
>> Knowledge Discovery and Management
>> * Classification Regression and Clustering
>> * Methodologies, Architectures or Computational Tools for
>> Business Intelligence
>> * Artificial Intelligence applied to Business Intelligence (e.g.
>> Knowledge Discovery, Evolutionary Computation, Intelligent Agents,
>> Fuzzy Logic)
>> * Data and Knowledge Visualization
>> * Temporal and Spatial Knowledge Discovery
>> * Data Pre-Processing Techniques for Knowledge Discovery and
>> Business Intelligence
>> * Bio-inspired and other cognitive related models, namely Neural
>> Networks.
>> * Bayesian Learning and Inductive Logic
>> * Incremental Learning, Change Detection and Learning from
>> Ubiquitous Data Streams
>> * Adaptive Business Intelligence
>> * Data Warehouse and OLAP
>> * Intelligent Decision Support Systems
>> * Learning in Neuro-Symbolic and Neural Computation Systems
>> * Real-word Applications (e.g. Prediction/Optimization in
>> Finance, Marketing, Sales, Production)
>>
>> Paper submission
>>
>> All submissions will be refereed and selected for presentation at
>> the conference on the basis of quality and relevance to the KDBI
>> issues. A selection of high quality full papers presented in the
>> different tracks will appear in a book published by Springer, in
>> the LNAI series. All remaining papers presented at the conference
>> will be published in a conference proceedings book.
>>
>> Submitted papers can be full-length papers or short papers. Full
>> papers can have a maximum length of 12 pages. Short papers can have
>> a maximum length of 4 pages. All papers should be prepared
>> according to the formatting instructions of Springer LNAI series (http://www.springer.com/computer/lncs?SGWID=0-164-7-72376-0
>> ). Authors should omit their names from the submitted papers, and
>> should take reasonable care to avoid indirectly disclosing their
>> identity.
>>
>> All papers should be submitted in PDF format through the conference
>> management website at: https://cmt.research.microsoft.com/EPIA2009
>>
>> Organising Committee
>>
>> * Nuno Marques, New University of Lisbon, Portugal (contact
>> person)
>> * Paulo Cortez, University of Minho, Portugal (contact person)
>> * Joao Moura Pires, New University of Lisbon, Portugal
>> * Luis Cavique, Univ. Aberta, Portugal
>> * Manuel Filipe Santos, DIS, University of Minho, Portugal
>> * Margarida Cardoso, ISCTE-Business School, Portugal
>> * Robert Stahlbock, DBE, University of Hamburg, Germany
>> * Zbigniew Michalewicz, SCS, University of Adelaide, Australia
>>
>> Contact: nmm[at]di[.]fct[.]unl[.]pt pcortez[at]dsi[.]uminho[.]pt
>>
>> Program Committee
>>
>> * Andre Ponce de Carvalho, Univ. Sao Paulo, Brazil
>> * Antonio Abelha, Univ. Minho, Portugal
>> * Armando Mendes, Univ. Acores, Portugal
>> * Armando Vieira, ISEP, Portugal
>> * Beatriz De la Iglesia, CMP, UEA, UK
>> * Carlos Alzate, K.U.Leuven, ESAT/SISTA, Belgium
>> * Carlos Soares, University of Porto, Portugal
>> * Cristian Figueroa-Sepulveda, Neo Metrics, Chile
>> * Emilio Carrizosa, University of Sevilla, Spain
>> * Ernestina Menasalvas, Universidad Politecnica de Madrid, Spain
>> * Fatima Rodrigues, ISEP, Portugal
>> * Gregory Wheeler, New Univ. of Lisbon, Portugal
>> * Joao Gama, University of Porto, Portugal
>> * Joao Pedro Neto, University of Lisbon, Portugal
>> * Joaquim Ferreira da Silva, New Univ. of Lisbon, Portugal
>> * Jose Costa, Federal University UFRN, Brazil
>> * Jose Neves, Univ. Minho, Portugal
>> * Jose Machado, Univ. Minho, Portugal
>> * Logbing Cao, University of Technology Sydney, Australia
>> * Mario Figueiredo, IT, IST, Portugal
>> * Murat Caner Testik, Hacettepe University, Turkey
>> * Ning Chen, Instituto Politecnico do Porto, Portugal
>> * Orlando Belo, Minho University, Portugal
>> * Pascal Hitzler, University of Karlsruhe,Germany
>> * Paulo Gomes, University of Coimbra, Portugal
>> * Peter Geczy, AIST, Japan
>> * Philippe Lenca, GET/ENST, France
>> * Rui Camacho, Universidade do Porto, Portugal
>> * Stefan Lessmann, Universit of Hamburg, Germany
>> * Stephane Lallich, Universit Lyon 2, France
>> * Theodore Trafalis, University of Oklahoma,USA
>> * Vasilis Aggelis, Piraeus Bank S.A., Greece
>> * Victor Alves, Univ. Minho, Portugal
>> * Vitor Lobo, Escola Naval, Portugal
>> * Wolfgang Jank, University of Maryland, USA
>> * Wolfram-M. Lippe, University of Muenster, Germany
>> ---
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