A hybrid approach to vietnamese word segmentation using part of speech tags

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A hybrid approach to vietnamese word segmentation using part of speech tags

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dc.contributor.author Pham, D.D.
dc.contributor.author Tran, G.B.
dc.contributor.author Pham, S.B.
dc.date.accessioned 2011-05-09T08:06:56Z
dc.date.available 2011-05-09T08:06:56Z
dc.date.issued 2009
dc.identifier.citation Page : 154-161 vi
dc.identifier.isbn 9.78E+12
dc.identifier.uri http://tainguyenso.vnu.edu.vn/jspui/handle/123456789/7285
dc.description.abstract Word segmentation is one of the most important tasks in NLP. This task, within Vietnamese language and its own features, faces some challenges, especially in words boundary determination. To tackle the task of Vietnamese word segmentation, in this paper, we propose the WS4VN system that uses a new approach based on Maximum matching algorithm combining with stochastic models using part-of-speech information. The approach can resolve word ambiguity and choose the best segmentation for each input sentence. Our system gives a promising result with an F-measure of 97%, higher than the results of existing publicly available Vietnamese word segmentation systems. ?? 2009 IEEE. vi
dc.language.iso en vi
dc.publisher KSE 2009 - The 1st International Conference on Knowledge and Systems Engineering vi
dc.subject F-measure vi
dc.subject Hybrid approach vi
dc.subject Boundary determination vi
dc.subject Maximum matchings vi
dc.title A hybrid approach to vietnamese word segmentation using part of speech tags vi
dc.type Article vi

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