Please use this identifier to cite or link to this item:
|Title: ||Using graph-kernels to represent semantic information in text classification|
|Authors: ||Gonçalves, Teresa|
|Issue Date: ||Jul-2009|
|Abstract: ||Most text classification systems use bag-of-words represen- tation of documents to find the classification target function. Linguistic structures such as morphology, syntax and semantic are completely ne- glected in the learning process.
This paper proposes a new document representation that, while includ- ing its context independent sentence meaning, is able to be used by a structured kernel function, namely the direct product kernel. The 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 de- scribing document’s significance has the same discriminative power over classes as the traditional bag-of-words approach.|
|Appears in Collections:||INF - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.