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Category:   E-CFP
Subject:   New Deadline: Special Issue Pattern Recognition
From:   Menno van Zaanen
Email:   mvzaanen_(on)_science.uva.nl
Date received:   11 Dec 2002
Deadline:   03 Jan 2003

***New Deadline: January 3, 2003*** CALL FOR PAPERS Pattern Recognition (The Journal of the Pattern Recognition Society) Special Issue on Grammatical Inference Techniques & Applications This Special Issue will be published in April, 2004 to commemorate and honor the memory of Late Professor K. S. Fu. Grammatical Inference (GI) is a collection of methodologies for learning grammars from training data. The most traditional field of application of GI has been syntactic pattern recognition. In the recent past, however, concerted efforts from diverse disciplines to find tractable inference techniques have added new dimensions and opened up unchartered territories. Applications of GI in more nontraditional fields include Gene Analysis, Sequence Prediction, Cryptography and Information Retrieval. Development of algorithms for GI has evolved over the years from dealing with only positive training samples to more fundamental efforts that try to circumvent the lack of negative samples.. This idea is pursued in stochastic grammars and languages which attempt to overcome absence of negative samples by gathering statistical information from available positive samples. Also within the framework of information theory, probability estimation technique for Hidden Markov Model known as Backward-Forward and for Context-Free language, the Inside-Outside algorithm are focal point of investigations in stochastic grammar field. Techniques that use intelligent search to infer the rules of grammar are showing considerable promise. Recently, there has been a surge of activities dealing with specialized neural network architecture and dedicated learning algorithms to approach GI problems. In more customary track, research in learning classes of transducers continue to arouse interests in GI community. Close interaction/collaboration between different disciplines and availability of powerful computers are fueling novel research efforts in GI. The objective of the Special Issue is to present the current status of this topic through the works of researchers in different disciplines. Original and tutorial papers are solicited that address theoretical and practical issues on this theme. Topics of interest include (but are not limited to): Theory: Neural network framework and learning algorithms geared to GI GI via heuristic and genetic search Inference mechanisms for stochastic grammars/languages Algebraic methods for identification of languages Transduction learning Applications: Image processing and computer vision Biosequence analysis and prediction Speech and natural language processing Data mining/information retrieval Optical character recognition Submission Procedure: Only electronic (ftp) submission will be accepted. Instructions for submission of papers can be found at the guest editor's web site (http://www-ee.ccny.cuny.edu/basu ). All submitted papers will be reviewed according to guidelines and standards of Pattern Recognition. Deadlines: Manuscript Submission: January 3, 2003 **** NEW DEADLINE *** Notification of Acceptance: April 16, 2003 Final Manuscript Due: June 16, 2003 Publication Date: April 2004 Guest Editor: Mitra Basu , The City College of CUNY, New York, U.S.A. basu_(on)_ccny.cuny.edu +-------------------------------------+ And all dared to brave unknown terrors, | Menno van Zaanen | to do mighty deeds, to boldly split | mvzaanen_(on)_science.uva.nl | infinitives that no man had split | http://www.science.uva. nl/%7Emvzaanen | before. -H'hikers Guide to the Galaxy
 

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