文章基本信息

标题：A Prior Model of Structural SVMs for Domain Adaptation
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作者：Lee, Chang-Ki ; Jang, Myung-Gil
期刊名称：ETRI Journal
印刷版ISSN：1225-6463
电子版ISSN：2233-7326
出版年度：2011
卷号：33
期号：5
页码：712-719
DOI：10.4218/etrij.11.0110.0571
语种：English
出版社：Electronics and Telecommunications Research Institute
摘要：In this paper, we study the problem of domain adaptation for structural support vector machines (SVMs). We consider a number of domain adaptation approaches for structural SVMs and evaluate them on named entity recognition, part-of-speech tagging, and sentiment classification problems. Finally, we show that a prior model for structural SVMs outperforms other domain adaptation approaches in most cases. Moreover, the training time for this prior model is reduced compared to other domain adaptation methods with improvements in performance.
关键词：Domain adaptation;structural SVMs;PRIOR model for structural SVMs