具有词汇特征的机器学习：Senseval-2的德卢斯方法
Machine Learning with Lexical Features: The Duluth Approach to Senseval-2
摘要：
本文介绍了在Senseval-2的词义消歧系统之间的比较练习中的16个德卢斯条目。在西班牙语和英语词汇样本任务中输入了八对德卢斯系统。这些都是基于标准的机器学习算法，这些算法从带有意义标签的训练文本中归纳出分类器，其中出现歧义词的上下文由简单的词汇特征表示。这些都是高度可移植的，强大的方法，可以作为更有针对性的方法的基础。
英文摘要：
This paper describes the sixteen Duluth entries in the Senseval-2 comparative exercise among word sense disambiguation systems. There were eight pairs of Duluth systems entered in the Spanish and English lexical sample tasks. These are all based on standard machine learning algorithms that induce classifiers from sense-tagged training text where the context in which ambiguous words occur are represented by simple lexical features. These are highly portable, robust methods that can serve as a foundation for more tailored approaches.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
