Multi-stage chinese collocation extraction

Rui Feng Xu; Qin Lu

Multi-stage chinese collocation extraction

Rui Feng Xu, Qin Lu

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

3 Citations (Scopus)

Abstract

Collocation is a recurrent and conventional natural language expression. In this research, Chinese collocations are categorized into four types. Based on the statistical analysis of different types of typical collocations, a multi-stage window-based collocation extraction system is designed, in which lexical statistic, synonyms information, syntactic information, and dependency knowledge, are used to extract n-gram collocations and different types of bi-gram collocations separately. Experimental results show that this system achieves a better precision and recall performance, compared with existed statistical collocation extraction techniques.

Original language	English
Title of host publication	2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005
Pages	3254-3259
Number of pages	6
Publication status	Published - 12 Dec 2005
Event	International Conference on Machine Learning and Cybernetics, ICMLC 2005 - Guangzhou, China Duration: 18 Aug 2005 → 21 Aug 2005

Conference

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

Keywords

Collocation extraction
Multi-stage extraction
Natural language processing

ASJC Scopus subject areas

General Engineering

Cite this

@inproceedings{d65b334ac84f4dc98932c43caa9b863d,

title = "Multi-stage chinese collocation extraction",

abstract = "Collocation is a recurrent and conventional natural language expression. In this research, Chinese collocations are categorized into four types. Based on the statistical analysis of different types of typical collocations, a multi-stage window-based collocation extraction system is designed, in which lexical statistic, synonyms information, syntactic information, and dependency knowledge, are used to extract n-gram collocations and different types of bi-gram collocations separately. Experimental results show that this system achieves a better precision and recall performance, compared with existed statistical collocation extraction techniques.",

keywords = "Collocation extraction, Multi-stage extraction, Natural language processing",

author = "Xu, {Rui Feng} and Qin Lu",

year = "2005",

month = dec,

day = "12",

language = "English",

isbn = "078039092X",

pages = "3254--3259",

booktitle = "2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005",

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

}

TY - GEN

T1 - Multi-stage chinese collocation extraction

AU - Xu, Rui Feng

AU - Lu, Qin

PY - 2005/12/12

Y1 - 2005/12/12

N2 - Collocation is a recurrent and conventional natural language expression. In this research, Chinese collocations are categorized into four types. Based on the statistical analysis of different types of typical collocations, a multi-stage window-based collocation extraction system is designed, in which lexical statistic, synonyms information, syntactic information, and dependency knowledge, are used to extract n-gram collocations and different types of bi-gram collocations separately. Experimental results show that this system achieves a better precision and recall performance, compared with existed statistical collocation extraction techniques.

AB - Collocation is a recurrent and conventional natural language expression. In this research, Chinese collocations are categorized into four types. Based on the statistical analysis of different types of typical collocations, a multi-stage window-based collocation extraction system is designed, in which lexical statistic, synonyms information, syntactic information, and dependency knowledge, are used to extract n-gram collocations and different types of bi-gram collocations separately. Experimental results show that this system achieves a better precision and recall performance, compared with existed statistical collocation extraction techniques.

KW - Collocation extraction

KW - Multi-stage extraction

KW - Natural language processing

UR - http://www.scopus.com/inward/record.url?scp=28444487992&partnerID=8YFLogxK

M3 - Conference article published in proceeding or book

SN - 078039092X

SN - 9780780390928

SP - 3254

EP - 3259

BT - 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005

T2 - International Conference on Machine Learning and Cybernetics, ICMLC 2005

Y2 - 18 August 2005 through 21 August 2005

ER -

Multi-stage chinese collocation extraction

Abstract

Conference

Keywords

ASJC Scopus subject areas

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