BISC: BISC seminar, Nov 29, 2001

From: masoud nikravesh (nikraves@eecs.berkeley.edu)
Date: Mon Nov 26 2001 - 14:48:57 MET

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    *********************************************************************
    Berkeley Initiative in Soft Computing (BISC)
    *********************************************************************

    Mining Spatial Data

    BISC Seminar
    Dr. Armand Prieditis, CEO
    Lookahead Decisions Incorporated

    Nov 29, 2001
    373 Soda Hall
    4:00-5:30pm

    Abstract:

    In a spatial database, the data at one location is likely to influence
    the data at nearby locations. As a result, spatial data requires
    special handling in the context of data mining. For example, spatial
    data usually violates the standard data mining assumption of
    an independent and identical distribution (iid). This talk describes an
    approach to data mining of spatial data using a new type of
    representation: Spatial Bayesian Networks (SBNs), which assume that the
    data is not iid and is instead distributed with certain
    spatial dependencies, semi-identically under four types of equivalence
    classes. Like their time-based cousins, Dynamic
    Bayesian Networks (DBNs), SBNs are a compact way to represent
    transitions. However, SBNs represent transitions over
    space rather than time. SBNs can also be used to learn from partial
    spatial data and, once learned, can be flexibly applied for
    inference.

    Short Bio:
    Dr. Prieditis is the Founder and CEO of the Lookahead Decisions
    Incorporated, A Factory Automation Software Company.
    He was the Chief Technology Officer (2000-2001)At Knowledgen, Inc, Palo
    Alto - A Knowledge Management Company;
    Founder and CEO (1998-2000) of Unconventional Wisdom , Davis, CA - A Web
    Data Mining Company; Senior Research
    Scientist (1998-1999) Institute for the Study of Learning and Expertise,
    Palo Alto, CA; Founder and Consultant
    (1993-present)Technology Tutorials, Davis, CA - Data mining consulting
    and training; Researcher (1998-1999) Computational
    Learning Laboratory, Stanford University, Stanford, CA; Assistant
    Professor (1990-1998) Computer Science Department,
    UC-Davis, CA.; Research Intern (1984-1985, summers)Siemens Research and
    Technology Center, Princeton, NJ.
    Dr. Prieditis has published in the leading Artificial Intelligence
    journals and has run prestigious data mining conferences. He has
    also developed web data mining software. This software learned from the
    user to retrieve relevant information from Google and
    the Open Directory. In addition, Dr. Prieditis' company, LDI, focuses on
    intelligent manufacturing and the application of data
    mining and other fuzzy reasoning methods for automated decision-making
    on the factory floor. Separate from Dr. Prieditis'
    academic credentials, he is a well respected entrepreneur.

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