SVM † ti ti 1-1 441-8580 † 619-0288 2-2-2 ATR †† E-mail: †gaizi@smlab.tutkie.tut.ac.jp, ††{kiyonori.ohtake,kazuhide.yamamoto}@atr.co.jp (SVM) MOZ YamCha Penn Chinese Treebank 10 YamCha 88% MOZ 4% 110 YamCha, MOZ 92%, 89% , YamCha, MOZ. Comparative Experiments of Chinese Analyzers between Support Vector Machines and Minimum Connective Costs Method Tatsumi YOSHIDA†, Kiyonori OHTAKE††, and Kazuhide YAMAMOTO†† † Dept. of Knowledge-based Information Engineering, Toyohashi University of Technology, 1-1 Hibarigaoka, Tenpaku-cho, Toyohashi-shi, Aichi, 441-8580 Japan. †† ATR Spoken Language Translation Research Laboratories, 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288 Japan. E-mail: †gaizi@smlab.tutkie.tut.ac.jp, ††{kiyonori.ohtake,kazuhide.yamamoto}@atr.co.jp We will report performances of the Chinese morphological analyzers using analysis tools and language Abstract resources, each of which is currently available to the public. We use YamCha, a tool based on Support Vector Ma- chines, and MOZ, which based on minimum connective costs method. We employ the Penn Chinese Treebank (100 thousand words), known as the most common Chinese language resource. Combining these tools and the resource, we measure the performances of Chinese morphological analysis, i.e., word segmentation and part-of-speech tagging. We found that the accuracy using YamCha attains around 88%, which is over 4% higher than that of MOZ, although it is computationally very expensive. We also employ the tagged corpus of Renmin Ribao (1.1 million words) that is bigger than the Penn Chinese Treebank. We found that the accuracies of morphological analysis by YamCha and MOZ attain around 92% and 89%, respectively. Chinese morphological analysis, Support Vector Machine, YamCha, MOZ. Key words 1. l YamCha CTB Penn Chinese Treebank SVM 1 2 Support Vector Machine
YamCha [6] YamCha YamCha [7] B I YamCha MOZ
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MOZ 1 http://cl.aist-nara.ac.jp/"taku-ku/software/yamcha/ http://cl.aist-nara.ac.jp/student/tatuo-y/ma/ 2 IOB2 http://cl.aist-nara.ac.jp/"taku-ku/software/TinySVM/ 3 CTB 2. o o 2 MOZ tri-gram (data sparseness) bi-gram Wi POSi C(wi, POSi) POSi   x C(x) (1) Wi w, POSi C(wi, POSi) p(w, | POS,) = C(POSi) (1) C(POS έ , POS έ ) POSi (2) POSシp(POS j | POS j ) = C(POS j , POS j ) C(POSi) 128 (3) p(wi | POSi) p(POS j | POS j ) = | / log ( )l (3) (4) 3. 2 CTB CTB 4181 9 10 YamCha MOZ 2 YamCha 3. 1 CTB 1 418 4 4181 CTB recall CPU: Pentium III 3 600 MHz : 256 MB   OS: Linux MOZ 3700 3 YamCha (5) (6) YamCha MOZ closed test open test
=  ———— × 100(%) — × 100(%) 2 10 10 1 10 10 6 precision 5 4  CTB 1 4185 4181 1 400 bi-gram (4) =  [| log( ) × 3. 1 (2) = [1
3.3 4. 10 10 11 11 5 2 ( ） t é MOZ null |USP(t i )| null USP(t i ) MOZ 33 CTB 10 1111 2954 MOZ 3. 4 YamCha MOZ 2 (F-measure) F 2 UK(t i )  w ∈ UK(t i ) U Seg(t i ) 6 1 MOZ 3. 4. 1 CTB 10 10 LOO 1 1 1 Leave One Out n n – 1 n
U Seg(t i ) w ∈ U Seg(t i ) USP(ti)
YamCha CTB 5 43913 1118794 7 1 2 11 CTB SVM 41 CTB 33 YamCha CTB F 87.9% http://www-nagao.kuee.kyoto-u.ac.jp/nl-resource/corpus.html 8 9 http://www-nagao.kuee.kyoto-u.ac.jp/nl-resource/juman.html
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11 10 YamCha JUMAN   9 39 PKU PKU PKU 8 1 1 CTB YamCha MOZ YamCha MOZ YamCha PKU PKU 101218 9 YamCha 128 1024 100 11 12 3993 JUMAN MOZ 4. 5 http://www.fujitsu.com.cn/support/ 6 44011 1121447 7 http://www.icl.pku.edu.cn/research/corpus/addition.htm
CTB CTB 11 3. 4. 2 10 PKU CTB CTB 1 11 LOO 10 MOZ 83.3% CTB MOZ 2 1 YamCha YamCha 51.1% MOZ YamCha
9 tri-gram YamCha YamCha YamCha
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2 12 CTB , 7, 3, pp. 39–56 (2000). U. H.-G. Kreßel: "Pairwise classification and support vec- [3] tor machines", Advances in Kernel Methods (Eds. by B. Schölkopf, C. J. Burges and A. J. Smola), The MIT Press, pp. 255–268 (1999). "Support vector machine chunk ", [4] , 2000-NL-140, pp. 9–16 (2000). “ ", [5] ,
2001-NL-142, pp. 97–104 (2001). "Support vector machine , 41, 4, pp. 1113–1123 s: " (2000). E. F. T. K. Sang and J. Veenstra:  "Representing text [7] chunks", Proceedings of EACL'99, pp. 173–179 (1999). [8] s: " , , 43 , 3, pp. 685–695 (2002). [1] T. Kudo and Y. Matsumoto: "Chunking with support vec- tor machines", Proceedings of the Second Meeting of the North American Chapter of the Association for Computa- tional Linguistics (2001). « [2] "," ,
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