On the Helmholtz Principle for Data Mining

 
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Old 10-08-2010
On the Helmholtz Principle for Data Mining

HPL-2010-133 On the Helmholtz Principle for Data Mining - Balinsky, Alexander; Balinsky, Helen; Simske, Steven
Keyword(s): extraction, feature extraction, unusual behavior detection, Helmholtz principle, mining textual and unstructured datasets
Abstract: We present novel algorithms for feature extraction and change detection in unstructured data, primarily in ...
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Paranoid::Data(3pm)					User Contributed Perl Documentation				       Paranoid::Data(3pm)

NAME
Paranoid::Data - Misc. Data Manipulation Functions VERSION
$Id: Data.pm,v 0.02 2010/04/15 23:23:28 acorliss Exp $ SYNOPSIS
$rv = deepCopy($sourceRef, $targetRef); DESCRIPTION
This module provides data manipulation functions, which at this time only consists of deepCopy. SUBROUTINES
/METHODS deepCopy $rv = deepCopy($sourceRef, $targetRef); This function performs a deep and safe copy of arbitrary data structures, checking for circular references along the way. Hashes and lists are safely duplicated while all other data types are just copied. This means that any embedded object references, etc., are identical in both the source and the target, which is probably not what you want. In short, this should only be used on pure hash/list/scalar value data structures. Both the source and the target reference must be of an identical type. This function returns the number of elements copied unless it runs into a problem (such as a circular reference), in which case it returns a zero. DEPENDENCIES
o Paranoid::Debug BUGS AND LIMITATIONS
AUTHOR
Arthur Corliss (corliss@digitalmages.com) LICENSE AND COPYRIGHT
This software is licensed under the same terms as Perl, itself. Please see http://dev.perl.org/licenses/ for more information. (c) 2009, Arthur Corliss (corliss@digitalmages.com) perl v5.14.2 2010-04-15 Paranoid::Data(3pm)