Neurocomputing: Special Issue on PATTERN RECOGNITION IN GRAPHICAL DOMAINS

Topics

Neurocomputing is seeking original and unpublished manuscripts for a Special Issue on "Pattern Recognition in Graphical Domains", scheduled for publication in June/July 2008.

Traditional machine learning applications usually cope with graphs by a preprocessing procedure that transforms structured data to simpler representations. This approach relies on what is called the "feature extraction" process, but it turns out to be quite unnatural for several situations where data are intrinsically organized as graphs, i.e. relationships exist among atomic sub-entities. Unfortunately, valuable information may be lost during the preprocessing and, as a consequence, classical methods may suffer from poor performance and generalization. Therefore, recursive or nested representations, as opposed to "flat" attribute-value data organizations, seem to be more adequate for many relevant problems arising from chemistry, bioinformatics, and the World Wide Web.
Recent studies on statistical pattern recognition and neural networks show possible directions to exploit structural information in problems which are inherently of sub-symbolic nature.

This special issue is intended to propose a critical re-thinking of the classic learning approaches and to investigate on possible new methodologies and applications of pattern recognition in graphical domains.

Submitted articles must not have been previously published and must not be currently submitted for publication elsewhere. Topics of interest include, but are not limited to, the following:

Neural Network Models for Graphs

Support Vector Machines and Kernel Methods for Graphs

Probabilistic Models for Graphs

Statistical Relational Learning

Pattern Recognition Applications Involving Graphical Data

Paper submission

Manuscript should follow the standard guidelines for Neurocomputing. Guidelines for formatting papers can be found in the Guide for Authors at http://www.elsevier.com/wps/find/journaldescription.cws_home/505628/authorinstructions. Prospective authors should submit an electronic copy of their complete manuscript through the Elsevier online submission system at http://ees.elsevier.com/neucom/. To ensure that all manuscripts are correctly identified for inclusion into the special issue, authors must select "Pattern Recognition" when they reach the "Article Type" step in the submission process.

Important Dates

New extended submission deadline: November 12th, 2007

First notification: January 25th, 2008

Revised manuscript submission: February 29th, 2008

Notification of final decision: April 11th, 2008

Final manuscript due: April 25th, 2008

Publication of the special issue: June/July 2008

Guest Editors

Monica Bianchini
University of Siena
Siena, Italy
E-mail: monica

dii

unisi

it

Franco Scarselli
University of Siena
Siena, Italy
E-mail: franco

dii

unisi

	NEUROCOMPUTING

	Call for Papers: Special Issue on PATTERN RECOGNITION IN GRAPHICAL DOMAINS

	Topics Neurocomputing is seeking original and unpublished manuscripts for a Special Issue on "Pattern Recognition in Graphical Domains", scheduled for publication in June/July 2008. Traditional machine learning applications usually cope with graphs by a preprocessing procedure that transforms structured data to simpler representations. This approach relies on what is called the "feature extraction" process, but it turns out to be quite unnatural for several situations where data are intrinsically organized as graphs, i.e. relationships exist among atomic sub-entities. Unfortunately, valuable information may be lost during the preprocessing and, as a consequence, classical methods may suffer from poor performance and generalization. Therefore, recursive or nested representations, as opposed to "flat" attribute-value data organizations, seem to be more adequate for many relevant problems arising from chemistry, bioinformatics, and the World Wide Web. Recent studies on statistical pattern recognition and neural networks show possible directions to exploit structural information in problems which are inherently of sub-symbolic nature. This special issue is intended to propose a critical re-thinking of the classic learning approaches and to investigate on possible new methodologies and applications of pattern recognition in graphical domains. Submitted articles must not have been previously published and must not be currently submitted for publication elsewhere. Topics of interest include, but are not limited to, the following: Neural Network Models for Graphs Support Vector Machines and Kernel Methods for Graphs Probabilistic Models for Graphs Statistical Relational Learning Pattern Recognition Applications Involving Graphical Data Paper submission Manuscript should follow the standard guidelines for Neurocomputing. Guidelines for formatting papers can be found in the Guide for Authors at http://www.elsevier.com/wps/find/journaldescription.cws_home/505628/authorinstructions. Prospective authors should submit an electronic copy of their complete manuscript through the Elsevier online submission system at http://ees.elsevier.com/neucom/. To ensure that all manuscripts are correctly identified for inclusion into the special issue, authors must select "Pattern Recognition" when they reach the "Article Type" step in the submission process. Important Dates New extended submission deadline: November 12th, 2007 First notification: January 25th, 2008 Revised manuscript submission: February 29th, 2008 Notification of final decision: April 11th, 2008 Final manuscript due: April 25th, 2008 Publication of the special issue: June/July 2008 Guest Editors Monica Bianchini University of Siena Siena, Italy E-mail: monicadiiunisiit Franco Scarselli University of Siena Siena, Italy E-mail: francodiiunisiit