In this paper, we present an algorithm that can classify large-scale text data with high classification quality and fast training speed. Our method is based on a novel extension o...
Dong Zhuang, Benyu Zhang, Qiang Yang, Jun Yan, Zhe...
Abstract. Standard Support Vector Machines (SVM) text classification relies on bag-of-words kernel to express the similarity between documents. We show that a document lattice can ...
In this paper we generalize the LARS feature selection method to the linear SVM model, derive an efficient algorithm for it, and empirically demonstrate its usefulness as a featur...
A machine-learning and a string-matching approach to automated subject classification of text were compared, as to their performance, advantages and downsides. The former approach ...
Background: The ability to distinguish between genes and proteins is essential for understanding biological text. Support Vector Machines (SVMs) have been proven to be very effici...
Tapio Pahikkala, Filip Ginter, Jorma Boberg, Jouni...