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Proceedings Paper

Autonomous journaling response using data model LUTS
Author(s): Holger Jaenisch; James Handley; Nathaniel Albritton; David Whitener; Randel Burnett; Robert Caspers; Stephen Moren; Thomas Alexander; William Maddox; William Albritton
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Paper Abstract

Matching journal entries to appropriate context responses can be a daunting problem, especially when there are no salient keyword matches between the entry and the proposed library of appropriate responses. We examine a real-world application for matching interactive journaling requests for guidance to an a priori established archive of sufficient multimedia responses. We show the analysis required to enable a Data Model based algorithm to group journaling entries according to intrinsic context information and type. We demonstrate a new lookup table (LUT) classifier that exploits all available data in LUT form.

Paper Details

Date Published: 13 April 2009
PDF: 11 pages
Proc. SPIE 7344, Data Mining, Intrusion Detection, Information Security and Assurance, and Data Networks Security 2009, 734409 (13 April 2009); doi: 10.1117/12.817863
Show Author Affiliations
Holger Jaenisch, LSEI Consultants (United States)
James Cook Univ. (Australia)
Amtec Corp. (United States)
James Handley, LSEI Consultants (United States)
Amtec Corp. (United States)
Nathaniel Albritton, Amtec Corp. (United States)
David Whitener, Phase IV (United States)
Randel Burnett, Amtec Corp. (United States)
Robert Caspers, Amtec Corp. (United States)
Stephen Moren, Amtec Corp. (United States)
Thomas Alexander, Amtec Corp. (United States)
William Maddox, Amtec Corp. (United States)
William Albritton, Amtec Corp. (United States)


Published in SPIE Proceedings Vol. 7344:
Data Mining, Intrusion Detection, Information Security and Assurance, and Data Networks Security 2009
Belur V. Dasarathy, Editor(s)

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