eprintid: 1777
rev_number: 9
eprint_status: archive
userid: 244
dir: disk0/00/00/17/77
datestamp: 2016-06-14 08:56:11
lastmod: 2016-06-14 08:56:11
status_changed: 2016-06-14 08:56:11
type: conference_item
metadata_visibility: show
creators_name: Ngo, Xuan Bach
creators_name: Le, Anh Cuong
creators_name: Nguyen, Viet Ha
creators_name: Nguyen, Ngoc Binh
creators_id: cuongla@vnu.edu.vn
creators_id: hanv@vnu.edu.vn
creators_id: nnbinh@vnu.edu.vn
title: Transformation Rule Learning without Rule Templates: A Case Study in Part of Speech Tagging
ispublished: pub
subjects: IT
divisions: fac_fit
abstract: Part of speech (POS) tagging is an important problem and is one of the first steps included in many tasks in natural language processing. It affects directly on the accuracy of many other problems such as Syntax Parsing, WordSense Disambiguation, and Machine Translation. Stochastic models solve this problem relatively well, but they still make mistakes. Transformation-based learning (TBL) is a solution which can be used to improve stochastic taggers by learning a set of transformation rules. However, its rule learning algorithm has the disadvantages that rule templates must be prepared by hand and only rules are instances of rule templates can be generated. In this paper, we propose a model to learn transformation rules without rule templates. This model considers the rule learning problem as a feature selection problem. Experiments on PennTree Bank showed that the proposal model reduces errors of stochastic taggers with some tags.
date: 2008
date_type: published
official_url: http://dx.doi.org/10.1109/ALPIT.2008.73
id_number: doi:10.1109/ALPIT.2008.73
full_text_status: none
pres_type: paper
pagerange: 9-14
event_title: Advanced Language Processing and Web Information Technology
event_dates: 2008
event_type: conference
refereed: TRUE
book_title: 2008 International Conference on Advanced Language Processing and Web Information Technology
citation:   Ngo, Xuan Bach and Le, Anh Cuong and Nguyen, Viet Ha and Nguyen, Ngoc Binh  (2008) Transformation Rule Learning without Rule Templates: A Case Study in Part of Speech Tagging.  In: Advanced Language Processing and Web Information Technology, 2008.