Information Retrieval Oriented Adaptive Chinese Word Segmentation System
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1 ISSN CODEN RUXUEW Joural of Softare Vol7 No3 March 2006 pp DOI: 0360/os70356 Tel/Fax: by Joural of Softare All rights reserved + ( Iformatio Retrieval Orieted Adaptive Chiese Word Segmetatio System CAO Yog-Gag + CAO Yu-Zhog JIN Mao-Zhog LIU Chao (School of Computer Sciece ad Egieerig BeiHag Uiversity Beiig Chia + Correspodig author: Ph: ext ygcao@csebuaaeduc Cao YG Cao YZ Ji MZ Liu C Iformatio retrieval orieted adaptive Chiese ord segmetatio system Joural of Softare 20067(3: Abstract: Ne ords recogitio ad ambiguity resolvig have vital effect o iformatio retrieval precisio This paper presets a statistical model based algorithm for adaptive Chiese ord segmetatio The a e ord segmetatio system called BUAASEISEG is desiged ad implemeted usig this algorithm BUAASEISEG ca recogize e ords i various domais ad do disambiguatio ad segmet ords ith arbitrary legth It uses a iterative bigram method to do ord segmetatio Through olie statistical aalysis o target article ad usig the offlie ords frequecies dictioary or the iverted idex of the search egie the cadidate ords selectio ad disambiguatio are doe O the basis of the statistical methods post-process usig stopords list quatity suffix ords list ad surame list are used for further precisio improvemet The comparative evaluatio ith the famous Chiese ord segmetatio system ICTCLAS usig es ad papers as testig text shos that BUAASEISEG outperforms ICTCLAS i e ords recogitio ad disambiguatio Key ords: : ord segmetatio system; ord segmetatio algorithm; iformatio retrieval; e ord recogitio; disambiguatio BUAASEISEG ICTCLAS BUAASEISEG : ; ; ; ; : TP39 : A Supported by the Natioal High-Tech Research ad Developmet Pla of Chia uder Grat No2004AA2030 ( (863 Received ; Accepted
2 : 357 [] : ( ; ( ICTCLAS [2] ( 5 Google ( Google ( 43 : BUAASEISEG BUAASEISEG ( BUAASEISEG : ; BUAASEISEG; ICTCLAS BUAASEISEG BUAASEISEG ; ICTCLAS BUAASEISEG : A m S i (0<i<=m :A={S S 2 S 3 S m } S i W i (0< S i = W i W i2 W i S i m S i m k k (0<k m W i W i C C C W [3] : m W = arg max P( W = C ( (gram gram
3 358 Joural of Softare Vol7 No3 March 2006 P P P 2 P 3 =!(!( 2!( 3! ( C S W = arg max P( W S = arg max P( W P( S W P(S = (3 : W = argmax P( W (4: Wˆ = argmax P( W = arg max m i= P( m i = argmax l P( i i= ICTCLAS [4] (4 (5 : Wˆ = arg max m i= l P( m m i arg max l( k / i k l i= l= k i ICTCLAS i (2 (3 (4 (5 k i i A BUAASEISEG ( (trasitio i P( i A 2 T ( = P( (6 i i 2 2 ( :4 6 ( 8 ( 3 (FSA ( BigramFilter FSA BigramFilter BigramFilter
4 : 359 (bootstrappig BUAASEISEG Text stream FSA FreqDict SurameList StopList ad QuatityWords BigramFilter FMMFilter Idex Fig Word segmetatio flo of BUAASEISEG BUAASEISEG 22 CDWS [5] 998 FSA 23 BigramFilter 2 ( BigramFilter (trasitio ( (5 C m i= m l P ( i = l P( i + l P( i= m 0<m<m S= CadiateBigram={CC2C2C3C3C4 C C} P(CC2 P(C2C3 (6 T(CC2 T(C2C3 C2C3 ; Bigram 2 (Bigram Bigram Gram -gram Bigram Bigram
5 360 Joural of Softare Vol7 No3 March 2006 :! ICTCLAS : BUAASEISEG < 2 2 Bigram 3 Bigram Bigram ; BUAASEISEG BUAASEISEG 24 Bigram (SW (Ci P L 3 :( P L (SW Ci=P L (Ci=P L (SW ;(2 2 P L (SW Ci<P L (Ci+P L (SW ;(3 2 P L (SW Ci P L (Ci 2 P L (SW Ci P L (SW (P L (SW Ci<P L (SW P L (SW Ci<P L (Ci ICTCLAS GATE( [6] FMMFilter ( ( 3 [7] : ICTCLAS ICTCLAS ICTCLAS ICTCLAS
6 : 36 BUAASEISEGR ( ~5; NASAC ( 6~9 : ( : ICTCLAS 3 Table Comparative evaluatio betee BUAASEISEG ad ICTCLAS BUAASEISEG ICTCLAS No Num of characters Num of ords Num of OOV ords Precisio of Precisio of BUAASEISEG (% ICTCLAS (% Nes Papers Both ~9 BUAASEISEG ; 5 BUAASEISEG ; 2 3 ICTCLAS BUAASEISEG ( ( BUAASEISEG BUAASEISEG ICTCLAS ICTCLAS ICTCLAS BUAASEISEG ; ICTCLAS BUAASEISEG ICTCLAS SCM [7] ICTCLAS ( / Viterbi SCM ICTCLAS ( / SCM
7 362 Joural of Softare Vol7 No3 March 2006 ( : [9] [0] ( BUAASEISEG [] BUAASEISEG JAVA C++ ICTCLAS ( JAVA C++ 0 [8] BUAASEISEG ICTCLAS 600 CWT00G( 30 G BUAASEISEG 4 BUAASEISEG ( 2 ( BUAASEISEG BUAASEISEG etork tutorig ( BUAASEISEG ( : ; ; CDWS Refereces: [] Foo S Li H Chiese ord segmetatio accuracy ad its effects o iformatio retrieval Iformatio Processig ad Maagemet (:6 90 [2] Zhag HP Yu HK Xiog DY Liu Q HHMM-Based Chiese lexical aalyzer ICTCLAS I: Proc of the 2d SigHa Workshop [3] Su KY Chaig TH Chag JS A overvie of corpus-based statistics-orieted (CBSO techiques for atual laguage processig Computatioal Liguistics ad Chiese Laguage Processig 996(:0 57
8 : 363 [4] Zhag HP Liu Q Model of Chiese ords rough segmetatio based o N-shortest-paths method Joural of Chiese Iformatio Processig 20026(5: 7 (i Chiese ith Eglish abstract [5] Liag NY CDWS: A ord segmetatio system for ritte Chiese texts Joural of Chiese Iformatio Processig 987(2: 0 06 (i Chiese ith Eglish abstract [6] Zhu XF Wag H Classificatio of moder Chiese quatity suffix ad ou Techical Report 994 (i Chiese ith Eglish abstract [7] Gao JF Li M Huag CN Improved source-chael models for Chiese ord segmetatio I: Proc of the 4st Aual Meetig of the Associatio for Computatioal Liguistics [8] Giles JT Wo L Berry MW GTP (geeral text parser Softare for text miig i statistical data miig ad koledge discovery I: Bozdoga H ed Boca Rato: CRC Press [9] Chag JS Li YC Su KY Automatic costructio of a Chiese electroic dictioary I: Yarosky D Church K eds Proc of the 3rd Workshop o Very Large Corpora [0] Dai YB Khoo SGT Loh TE A e statistical formula for Chiese ord segmetatio icorporatig cotextual iformatio I: Proc of the 22d Aual It l ACM SIGIR Cof o Research ad Developmet i Iformatio Retrieval [] Gao JF Wu AD Li M Huag CN Li HQ Xia XS Qi HW Adaptive Chiese ord segmetatio I: Proc of the 4st Aual Meetig of the Associatio for Computatioal Liguistics : [4] N (5: 7 [5] CDWS 987(2:0 06 [6] collectio-2/yyy23htm (977 / (94 (978 (958 CCF
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