1. Web
{jmiyake, kotsukam, msassano}@yahoo-corp.jp
1
Web
1
Web
3
SVM
2
Bergsma [1] 3.1
SVM
Tan [2] 1
Web 5-gram
Wikipedia
Wang [3] Microsoft Web N-gram
Web CountDown

2. 1:
0.915
0.03
0.02
0.013
0.011
... ...
1:
1
2
1
0.1%
iphone4 iphone 4
3-gram
3-gram
n-gram q
Q q xi N
3.2
q = {x0 , x1 , x2 , ..., xN } q∈Q
3.2.1 3-gram
Q
1 2
q
1
∑N
i=1 log P (xi |xi−2 , xi−1 )
max
2 Web q∈Q N −1
3.2.2
( + +
Web
)

3. 2:
2010 10 1 31
615 Wikipedia
82.4 %
2010 10 1 31
20
4 SVM
3:
Qry-Acc Seg-Acc
0.645 0.937
0.617 0.923
0.731 0.951
0.732 0.953 SVM
+ 0.739 0.952
+ 0.773 0.962
+ 0.781 0.962
Web 4.1 SVM
SVM Sassano[4]
Neubig [5]
1
( +
) Bergsma Query n-gram n-gram
Accuracy(Qry-Acc) Segment Accuracy(Seg-Acc) SVM
Qry-Acc Seg-
Acc
0.9
2 1 4.1.1
10 2 SVM
n-gram
100% 5% xi , xi+1
600 w
2 xi−w+1 , .., xi , xi+1 , ..., xi+w n-gram
3 n-gram
+ Qry-Acc Seg-Acc n-gram
+
n-gram
1 Yahoo! Japan
Web API n-gram
http://developer.yahoo.co.jp/webapi/jlp/ma/v1/parse.html

4. 4: SVM 5: SVM
Qry-Acc Seg-Acc
2010 10 1 31 + 0.659 0.943
10 + 0.667 0.945
2010 10 1 31
20
5
SVM liblinear
xi , xi+1
R
L xi , xi+1 I Web
ipadic-2.7.0-20070801
Wikipedia
( Wikpedia:
2 Wikipedia: 10 ) SVM
4.2
SVM
SVM
1 Web
[1] S. Bergsma and Q.I. Wang. Learning noun phrase
10 query segmentation. In Proc. of EMNLP-CoNLL,
( + + 2007.
) 4 [2] B. Tan and F. Peng. Unsupervised query seg-
Qry-Acc Seg-Acc mentation using generative language models and
SVM liblinear[6] wikipedia. In Proceeding of the 17th internatio-
nal conference on World Wide Web, pp. 347–356.
5 n-gram
ACM, 2008.
3
[3] K. Wang, C. Thrasher, E. Viegas, X. Li, and
B.P. Hsu. An overview of Microsoft web N-gram
corpus and applications. In Proceedings of the
4.3 NAACL HLT 2010 Demonstration Session, pp.
45–48. Association for Computational Linguis-
5 + tics, 2010.
[4] M. Sassano. An empirical study of active learning
with support vector machines for Japanese word
segmentation. In Proceedings of the 40th Annual
Meeting on Association for Computational Lin-
guistics, pp. 505–512. Association for Computa-
tional Linguistics, 2002.
[5] Graham Neubig, , .
.
16 (NLP2010), , 3 2010.
[6] R.E. Fan, K.W. Chang, C.J. Hsieh, X.R. Wang,
and C.J. Lin. LIBLINEAR: A library for large
linear classification. The Journal of Machine Le-
arning Research, Vol. 9, pp. 1871–1874, 2008.