A multi-stage Chinese collocation extraction system

Ruifeng Xu; Qin Lu

A multi-stage Chinese collocation extraction system

Ruifeng Xu, Qin Lu

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

7 Citations (Scopus)

Abstract

Most of the existing collocation extraction systems are based on globally significant statistical behaviors without mechanisms to handle different types of collocations. By taking compositionality, substitutability, modifiability and internal associations into consideration, collocations are categorized into four different types in this work. Based on the analysis for each type of collocation, a multi-stage extraction system is designed using different combinations of discriminative features so as to identify different types of collocations in different stages. Perceptron training is employed to optimize the consolidation of discriminative features from different sources. Experiment results show that the achieved performance is much better than most reported work.

Original language	English
Title of host publication	Advances in Machine Learning and Cybernetics - 4th International Conference, ICMLC 2005, Revised Selected Papers
Pages	740-749
Number of pages	10
Publication status	Published - 14 Jul 2006
Event	4th International Conference on Machine Learning and Cybernetics, ICMLC 2005 - Guangzhou, China Duration: 18 Aug 2005 → 21 Aug 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3930 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Conference on Machine Learning and Cybernetics, ICMLC 2005
Country/Territory	China
City	Guangzhou
Period	18/08/05 → 21/08/05

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Cite this

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title = "A multi-stage Chinese collocation extraction system",

abstract = "Most of the existing collocation extraction systems are based on globally significant statistical behaviors without mechanisms to handle different types of collocations. By taking compositionality, substitutability, modifiability and internal associations into consideration, collocations are categorized into four different types in this work. Based on the analysis for each type of collocation, a multi-stage extraction system is designed using different combinations of discriminative features so as to identify different types of collocations in different stages. Perceptron training is employed to optimize the consolidation of discriminative features from different sources. Experiment results show that the achieved performance is much better than most reported work.",

author = "Ruifeng Xu and Qin Lu",

year = "2006",

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note = "4th International Conference on Machine Learning and Cybernetics, ICMLC 2005 ; Conference date: 18-08-2005 Through 21-08-2005",

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Xu, R & Lu, Q 2006, A multi-stage Chinese collocation extraction system. in Advances in Machine Learning and Cybernetics - 4th International Conference, ICMLC 2005, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3930 LNAI, pp. 740-749, 4th International Conference on Machine Learning and Cybernetics, ICMLC 2005, Guangzhou, China, 18/08/05.

A multi-stage Chinese collocation extraction system. / Xu, Ruifeng; Lu, Qin.
Advances in Machine Learning and Cybernetics - 4th International Conference, ICMLC 2005, Revised Selected Papers. 2006. p. 740-749 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3930 LNAI).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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N2 - Most of the existing collocation extraction systems are based on globally significant statistical behaviors without mechanisms to handle different types of collocations. By taking compositionality, substitutability, modifiability and internal associations into consideration, collocations are categorized into four different types in this work. Based on the analysis for each type of collocation, a multi-stage extraction system is designed using different combinations of discriminative features so as to identify different types of collocations in different stages. Perceptron training is employed to optimize the consolidation of discriminative features from different sources. Experiment results show that the achieved performance is much better than most reported work.

AB - Most of the existing collocation extraction systems are based on globally significant statistical behaviors without mechanisms to handle different types of collocations. By taking compositionality, substitutability, modifiability and internal associations into consideration, collocations are categorized into four different types in this work. Based on the analysis for each type of collocation, a multi-stage extraction system is designed using different combinations of discriminative features so as to identify different types of collocations in different stages. Perceptron training is employed to optimize the consolidation of discriminative features from different sources. Experiment results show that the achieved performance is much better than most reported work.

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M3 - Conference article published in proceeding or book

SN - 3540335846

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 740

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BT - Advances in Machine Learning and Cybernetics - 4th International Conference, ICMLC 2005, Revised Selected Papers

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ER -

A multi-stage Chinese collocation extraction system

Abstract

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Conference

ASJC Scopus subject areas

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