We propose to solve a text categorization task using a new metric between documents, based on a priori semantic knowledge about words. This metric can be incorporated into the def...
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...
Question classification is very important for question answering. This paper presents our research work on automatic question classification through machine learning approaches. W...
Due to the lack of annotated data sets, there are few studies on machine learning based approaches to extract named entities (NEs) in clinical text. The 2009 i2b2 NLP challenge is...
In this paper, we propose a support vector machine with automatic confidence (SVMAC) for gender classification based on facial images. Namely, we explore how to incorporate confide...