Using Graph-Kernels to Represent Semantic Information in Text Classification

摘要

Most text classification systems use bag-of-words representation of documents to find the classification target function. Linguistic structures such as morphology, syntax and semantic are completely neglected in the learning process.rnThis paper proposes a new document representation that, while including its context independent sentence meaning, is able to be used by a structured kernel function, namely the direct product kernel.rnThe proposal is evaluated using a dataset of articles from a Portuguese daily newspaper and classifiers are built using the SVM algorithm. The results show that this structured representation, while only partially describing document's significance has the same discriminative power over classes as the traditional bag-of-words approach.