.png){kind=icon}
Return
Factored sequence kernels
.png){kind=icon}
PRE
AI
DOI：10.1016/j.neucom.2008.11.025.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper we propose an extension of sequence kernels to the case where the symbols that define the sequences have multiple representations. This configuration occurs, for instance, in natural language processing, where words can be characterized according to different linguistic dimensions. The core of our contribution is to integrate early the different representations in the kernel, in a way that generates rich composite features defined across the various symbol dimensions. (C) 2009 Elsevier B.V. All rights reserved.
Keywords:
Machine learning
Kernel methods
Sequence kernels
Factored kernels
Language modeling
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6.5
Papers:
2.5W
Citations:
6.5W
.png){kind=icon}
