Text classification with a Primal SVM endowed with domain knowledge
نویسندگان
چکیده
In this paper we solve a document classification task by incorporating prior/domain knowledge onto the SVM. The algorithm consists in to learn a prior classifier in the primal space (words) from an ‘external’ source of information to the text classification itself: patterns of reader’s eyes movements when reading relevant words for discriminating texts. This prior weight vector is then plugged into the SVM optimisation in the primal space. Experimental results include a comparison of the proposed algorithm with plain SVM classifiers and with an alternative way of mixing textual and eye information based on the SVM-2K.
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