Paper
11 April 2008 Formal analytical modeling of blog content as personal narrative
Michael J. Coombs, Holger M. Jaenisch, James W. Handley
Author Affiliations +
Abstract
This paper contrasts two techniques for analyzing blog content and making use of this information to model blog content. One method uses classical text content and analysis presented for human interpretation. The second method relies on a data mined list of descriptive words characterizing the blogs. We examine the use of different data mining tools, Kryltech's "Subject Search Summarizer", Leximancer, and QUEST, to provide orthogonal and independently generated key word lists. These lists are then converted into Data Models, enabling mathematical modeling of blog content.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael J. Coombs, Holger M. Jaenisch, and James W. Handley "Formal analytical modeling of blog content as personal narrative", Proc. SPIE 6965, Modeling and Simulation for Military Operations III, 69650D (11 April 2008); https://doi.org/10.1117/12.775563
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Data modeling

Mathematical modeling

Analytical research

Chaos

Mining

Chronology

Data mining

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