Paper: Part of Speech Tagging Using a Network of Linear Separators

ACL ID P98-2186
Title Part of Speech Tagging Using a Network of Linear Separators
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1998
Authors

We present an architecture and an on-line learning algorithm and apply it to the problem of part-of- speech tagging. The architecture presented, SNOW, is a network of linear separators in the feature space, utilizing the Winnow update algorithm. Multiplicative weight-update algorithms such as Winnow have been shown to have exceptionally good behavior when applied to very high dimensional problems, and especially when the target concepts depend on only a small subset of the features in the feature space. In this paper we describe an architec- ture that utilizes this mistake-driven algorithm for multi-class prediction - selecting the part of speech of a word. The experimental analysis presented here provides more evidence to that these algorithms are suitable for natural language problems. T...