13 April 2009Autonomous journaling response using data model LUTS
Holger Jaenisch, James Handley, Nathaniel Albritton, David Whitener, Randel Burnett, Robert Caspers, Stephen Moren, Thomas Alexander, William Maddox III, William Albritton Jr.
Holger Jaenisch,1,2,3 James Handley,1,3 Nathaniel Albritton,3 David Whitener,4 Randel Burnett,3 Robert Caspers,3 Stephen Moren,3 Thomas Alexander,3 William Maddox III,3 William Albritton Jr.3
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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.
Holger Jaenisch,James Handley,Nathaniel Albritton,David Whitener,Randel Burnett,Robert Caspers,Stephen Moren,Thomas Alexander,William Maddox III, andWilliam Albritton Jr.
"Autonomous journaling response using data model LUTS", Proc. SPIE 7344, Data Mining, Intrusion Detection, Information Security and Assurance, and Data Networks Security 2009, 734409 (13 April 2009); https://doi.org/10.1117/12.817863
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Holger Jaenisch, James Handley, Nathaniel Albritton, David Whitener, Randel Burnett, Robert Caspers, Stephen Moren, Thomas Alexander, William Maddox III, William Albritton Jr., "Autonomous journaling response using data model LUTS," Proc. SPIE 7344, Data Mining, Intrusion Detection, Information Security and Assurance, and Data Networks Security 2009, 734409 (13 April 2009); https://doi.org/10.1117/12.817863