Data fusion and classification using a hybrid intrinsic cellular inference network

Robert Woodley; Brett Walenz; John Seiffertt; Paul Robinette; Donald Wunsch

doi:10.1117/12.852666

28 April 2010 Data fusion and classification using a hybrid intrinsic cellular inference network

Robert Woodley, Brett Walenz, John Seiffertt, Paul Robinette, Donald Wunsch

Proceedings Volume 7710, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2010; 771005 (2010) https://doi.org/10.1117/12.852666
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

Hybrid Intrinsic Cellular Inference Network (HICIN) is designed for battlespace decision support applications. We developed an automatic method of generating hypotheses for an entity-attribute classifier. The capability and effectiveness of a domain specific ontology was used to generate automatic categories for data classification. Heterogeneous data is clustered using an Adaptive Resonance Theory (ART) inference engine on a sample (unclassified) data set. The data set is the Lahman baseball database. The actual data is immaterial to the architecture, however, parallels in the data can be easily drawn (i.e., "Team" maps to organization, "Runs scored/allowed" to Measure of organization performance (positive/negative), "Payroll" to organization resources, etc.). Results show that HICIN classifiers create known inferences from the heterogonous data. These inferences are not explicitly stated in the ontological description of the domain and are strictly data driven. HICIN uses data uncertainty handling to reduce errors in the classification. The uncertainty handling is based on subjective logic. The belief mass allows evidence from multiple sources to be mathematically combined to increase or discount an assertion. In military operations the ability to reduce uncertainty will be vital in the data fusion operation.

Citation Download Citation

Robert Woodley, Brett Walenz, John Seiffertt, Paul Robinette, and Donald Wunsch "Data fusion and classification using a hybrid intrinsic cellular inference network", Proc. SPIE 7710, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2010, 771005 (28 April 2010); https://doi.org/10.1117/12.852666

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available