Maintaining the Influence of Context Matrix Construction Principles on the Ability of Linguistic Feature Extraction by ICA

Blind signal separation (BSS) based on independent component analysis (ICA) is an emerging approach which application is not limited to the signal processing research, where its application principle is rather straight forward. For an increasing amount of information processing fields, ICA has meaningful application which are still undiscovered. The aim of this paper is to investigate the ability of linguistic feature extraction based on word context preprocessing by ICA. The work refers to a first brief analysis in which ICA was applied to an English corpus. We continue this analysis depending on the number of components and the amount of syntactical informations that we take into account. Further more we discuss to which extent the results deliver either general linguistic features, or linguistic features giving us information about the text.