Kolenda, Thomas

The thesis investigates the role of independent component analysis in the setting of virtual environments, with the purpose of finding properties that reflect human context. A general framework for performing unsupervised classification with ICA is presented in extension to the latent semantic indexing model. Evidence is found that the separation by independence presents a hierarchical structure that relates to context in a human sense. Furthermore, introducing multiple media modalities, a combined structure was found to reflect context description at multiple levels. Different ICA algorithms were compared to investigate computational differences and separation results. The ICA properties were finally implemented in a chat room analysis tool and briefly investigated for visualization of search engines results

Online Research Database In Technology

Adaptive tools in virtual environments: Independent component analysis for multimedia

http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.128.4240

Adaptive tools in virtual environments: Independent component analysis for multimedia

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Online Research Database In Technology