NDLI: iSentenizer: An incremental sentence boundary classifier

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2011 7th International Conference on Natural Language Processing and Knowledge Engineering

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)

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iSentenizer: An incremental sentence boundary classifier

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International Conference on Natural Language Processing and Knowledge Engineering, 2003. Proceedings. 2003

iSentenizer: An incremental sentence boundary classifier

Content Provider	IEEE Xplore Digital Library
Author	Fai Wong Chao, S.
Copyright Year	2010
Description	Author affiliation: CIS, University of Macau, China (Fai Wong; Chao, S.)
Abstract	In this paper, we revisited the topic of sentence boundary detection, and proposed an incremental approach to tackle the problem. The boundary classifier is revised on the fly to adapt to the text of high variety of sources and genres. We applied $i^{+}Learning,$ an incremental algorithm, for constructing the sentence boundary detection model using different features based on local context. Although the model can be easily trained on any genre of text and on any alphabet language, we emphasize the ability that the classifier is adaptable to text with domain and topic shifts without retraining the whole model from scratch. Empirical results indicate that the performance of proposed system is comparable to that of similar systems.
Starting Page	1
Ending Page	7
File Size	204924
Page Count	7
File Format	PDF
ISBN	9781424468966
e-ISBN	9781424468997
DOI	10.1109/NLPKE.2010.5587856
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	tagging incremental learning Artificial neural networks Variable speed drives Tagging $i^{+}Learning$ sentence boundary detection
Content Type	Text
Resource Type	Article

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