[Corpora-List] Call for papers: Special Issue Pattern Recognition

From: Menno van Zaanen (mvzaanen@science.uva.nl)
Date: Tue Oct 15 2002 - 16:51:03 MET DST

  • Next message: Yuri Tambovtsev: "[Corpora-List] How to get German texts in electronic form?"

    Apologies for Multiple Copies.

    Please distribute...

    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 will be posted on November 10 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: December 10, 2002
    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@ccny.cuny.edu

    +-------------------------------------+
    | Menno van Zaanen | "Let him not vow to walk in the dark,
    | mvzaanen@science.uva.nl | who has not seen the nightfall."
    | http://www.science.uva.nl/~mvzaanen | -Elrond



    This archive was generated by hypermail 2b29 : Tue Oct 15 2002 - 17:19:44 MET DST