Knowledge Discovery in Databases: PKDD 2005 : 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, October 3-7, 2005, Proceedings

Alipio Jorge

ISBN 10: 3540292446 / ISBN 13: 9783540292449

Edité par Springer, Berlin, Springer, 2005

A propos de cet article

Neuware - The European Conference on Machine Learning (ECML) and the European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) were jointly organized this year for the fth time in a row, after some years of mutual independence before. After Freiburg (2001), Helsinki (2002), Cavtat (2003) and Pisa (2004), Porto received the 16th edition of ECML and the 9th PKDD in October 3-7. Having the two conferences together seems to be working well: 585 di erent paper submissions were received for both events, which maintains the high s- mission standard of last year. Of these, 335 were submitted to ECML only, 220 to PKDD only and 30 to both. Such a high volume of scienti c work required a tremendous e ort from Area Chairs, Program Committee members and some additional reviewers. On average, PC members had 10 papers to evaluate, and Area Chairs had 25 papers to decide upon. We managed to have 3 highly qua- edindependentreviewsperpaper(withveryfewexceptions)andoneadditional overall input from one of the Area Chairs. After the authors' responses and the online discussions for many of the papers, we arrived at the nal selection of 40 regular papers for ECML and 35 for PKDD. Besides these, 32 others were accepted as short papers for ECML and 35 for PKDD. This represents a joint acceptance rate of around 13% for regular papers and 25% overall. We thank all involved for all the e ort with reviewing and selection of papers. Besidesthecoretechnicalprogram,ECMLandPKDDhad6invitedspeakers, 10 workshops, 8 tutorials and a Knowledge Discovery Challenge.

N° de réf. du vendeur 9783540292449

Détails bibliographiques

• Titre: Knowledge Discovery in Databases: PKDD 2005 : 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, October 3-7, 2005, Proceedings
• Éditeur: Springer, Berlin, Springer
• Date de parution: 2005
• Langue: anglais
• ISBN à 10 chiffres: 3540292446
• ISBN à 13 chiffres: 9783540292449
• Reliure: Taschenbuch
• État de l'article: Neu
• Dimensions: 235 L x 155 H x 35 P (en millimètres) 235 millimètres de largeur par 155 millimètres de hauteur par 35 millimètres de profondeur
• Poids: 1030 grammes

A propos de ce titre

Synopsis

The European Conference on Machine Learning (ECML) and the European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) were jointly organized this year for the ?fth time in a row, after some years of mutual independence before. After Freiburg (2001), Helsinki (2002), Cavtat (2003) and Pisa (2004), Porto received the 16th edition of ECML and the 9th PKDD in October 3-7. Having the two conferences together seems to be working well: 585 di?erent paper submissions were received for both events, which maintains the high s- mission standard of last year. Of these, 335 were submitted to ECML only, 220 to PKDD only and 30 to both. Such a high volume of scienti?c work required a tremendous e?ort from Area Chairs, Program Committee members and some additional reviewers. On average, PC members had 10 papers to evaluate, and Area Chairs had 25 papers to decide upon. We managed to have 3 highly qua- ?edindependentreviewsperpaper(withveryfewexceptions)andoneadditional overall input from one of the Area Chairs. After the authors' responses and the online discussions for many of the papers, we arrived at the ?nal selection of 40 regular papers for ECML and 35 for PKDD. Besides these, 32 others were accepted as short papers for ECML and 35 for PKDD. This represents a joint acceptance rate of around 13% for regular papers and 25% overall. We thank all involved for all the e?ort with reviewing and selection of papers. Besidesthecoretechnicalprogram, ECMLandPKDDhad6invitedspeakers, 10 workshops, 8 tutorials and a Knowledge Discovery Challenge.