Entry Chen:2009:USD from talip.bib
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BibTeX entry
@Article{Chen:2009:USD,
author = "Wenliang Chen and Daisuke Kawahara and Kiyotaka
Uchimoto and Yujie Zhang and Hitoshi Isahara",
title = "Using Short Dependency Relations from Auto-Parsed Data
for {Chinese} Dependency Parsing",
journal = j-TALIP,
volume = "8",
number = "3",
pages = "10:1--10:??",
month = aug,
year = "2009",
CODEN = "????",
DOI = "https://doi.org/10.1145/1568292.1568293",
ISSN = "1530-0226 (print), 1558-3430 (electronic)",
ISSN-L = "1530-0226",
bibdate = "Mon Mar 29 15:37:08 MDT 2010",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/talip.bib",
abstract = "Dependency parsing has become increasingly popular for
a surge of interest lately for applications such as
machine translation and question answering. Currently,
several supervised learning methods can be used for
training high-performance dependency parsers if
sufficient labeled data are available.\par
However, currently used statistical dependency parsers
provide poor results for words separated by long
distances. In order to solve this problem, this article
presents an effective dependency parsing approach of
incorporating short dependency information from
unlabeled data. The unlabeled data is automatically
parsed by using a deterministic dependency parser,
which exhibits a relatively high performance for short
dependencies between words. We then train another
parser that uses the information on short dependency
relations extracted from the output of the first
parser. The proposed approach achieves an unlabeled
attachment score of 86.52\%, an absolute 1.24\%
improvement over the baseline system on the Chinese
Treebank data set. The results indicate that the
proposed approach improves the parsing performance for
longer distance words.",
acknowledgement = ack-nhfb,
articleno = "10",
fjournal = "ACM Transactions on Asian Language Information
Processing",
journal-URL = "http://portal.acm.org/browse_dl.cfm?&idx=J820",
keywords = "Chinese dependency parsing; semi-supervised learning;
unlabeled data",
}
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8(1)3,
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8(2)9,
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6(3)9,
6(3)11,
6(4)1,
7(1)2,
7(2)7,
7(3)10,
8(1)2,
8(2)9,
8(4)19,
9(1)1,
9(1)3,
9(2)5,
9(4)13,
10(1)2,
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12(2)7,
12(3)12,
12(4)16,
12(4)17,
13(2)6,
13(2)8,
13(3)13,
13(4)18
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7(1)2,
8(2)9,
8(3)12,
9(2)5,
9(3)11,
9(3)12,
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13(1)2,
13(1)3,
13(1)4
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8(2)8,
8(4)17,
9(2)6,
10(3)14
- result,
4(2)135,
5(2)121,
5(2)146,
5(2)165,
6(2)6,
6(2)7,
6(3)9,
6(3)11,
6(4)3,
7(1)2,
7(2)5,
7(2)6,
7(2)7,
7(3)8,
7(3)10,
7(4)11,
7(4)12,
7(4)13,
8(1)2,
8(1)3,
8(1)4,
8(2)6,
8(2)9,
8(3)12,
8(4)14,
8(4)15,
8(4)16,
8(4)17,
8(4)18,
8(4)19,
9(1)1,
9(1)2,
9(2)5,
9(2)6,
9(2)7,
9(3)11,
9(3)12,
9(4)14,
10(1)2,
10(2)7,
11(2)4,
11(2)5,
11(3)8,
11(3)9,
11(3)11,
11(4)13,
11(4)14,
11(4)15,
12(1)3,
12(1)4,
12(2)5,
12(2)7,
12(3)9,
12(3)10,
12(3)11,
12(4)14,
12(4)16,
13(1)1,
13(1)4,
13(2)6,
13(2)7,
13(2)9,
13(3)11,
13(3)12,
13(3)14
- score,
7(2)7,
7(4)12,
8(2)7,
9(1)3,
9(2)6,
10(4)18,
11(2)6,
12(3)9,
12(4)17,
13(1)2,
13(3)13,
13(4)16
- semi-supervised,
11(2)7,
12(2)7
- set,
1(3)269,
5(2)121,
6(1)z,
7(1)3,
7(3)8,
7(4)11,
7(4)13,
8(3)12,
8(4)15,
9(1)1,
9(1)3,
9(2)5,
10(1)4,
10(2)8,
10(4)20,
11(2)5,
11(2)7,
11(3)10,
11(3)11,
11(4)13,
11(4)14,
12(1)2,
12(1)4,
12(3)9,
13(2)8,
13(2)9,
13(3)12,
13(3)13,
13(4)17
- several,
6(2)6,
6(2)7,
6(4)3,
7(2)5,
7(2)7,
7(3)10,
8(4)16,
8(4)17,
8(4)18,
9(3)12,
11(2)6,
11(4)13,
11(4)16,
12(1)2,
13(3)12,
13(3)14
- short,
8(3)12,
8(4)14,
12(1)2
- solve,
6(2)7,
10(4)20,
11(3)8,
12(3)10,
12(3)12,
12(4)16
- statistical,
1(1)3,
3(2)87,
3(4)243,
5(2)121,
5(4)323,
5(4)360,
6(1)z-4,
7(1)1,
8(1)2,
8(1)4,
8(2)6,
8(2)7,
8(2)8,
8(2)9,
8(4)15,
8(4)19,
9(2)6,
9(2)7,
9(3)11,
10(4)18,
11(2)6,
11(2)7,
11(3)8,
11(4)15,
12(1)1,
12(3)12,
12(4)14,
12(4)16,
12(4)17,
13(1)2,
13(1)3,
13(1)4,
13(4)17
- such,
7(2)7,
7(3)8,
7(3)10,
7(4)12,
8(2)8,
8(3)11,
8(3)12,
8(4)14,
8(4)16,
8(4)17,
9(1)1,
9(3)12,
9(4)13,
9(4)15,
10(1)5,
10(2)8,
10(3)12,
10(4)21,
11(1)2,
11(2)5,
11(2)7,
11(3)8,
11(3)10,
11(3)11,
11(4)13,
11(4)16,
11(4)17,
11(4)18,
12(1)1,
12(1)2,
12(2)6,
12(3)10,
12(3)11,
12(4)14,
12(4)17,
13(1)1,
13(3)12,
13(4)17
- sufficient,
7(4)11
- supervised,
6(2)6,
8(1)3,
9(1)2,
9(1)4,
11(2)4,
13(1)3,
13(2)9
- supervised, semi-,
11(2)7,
12(2)7
- then,
5(2)121,
6(2)6,
7(1)1,
7(3)10,
7(4)12,
8(1)4,
8(2)7,
8(3)11,
8(3)12,
8(4)14,
9(1)1,
9(2)7,
9(3)11,
10(2)7,
10(3)13,
10(4)20,
11(1)3,
11(2)7,
11(3)11,
11(4)15,
12(1)3,
12(3)10,
12(4)17,
13(1)4,
13(2)9,
13(3)13,
13(4)16
- train,
7(2)6,
12(3)9
- training,
5(2)121,
6(3)11,
7(1)1,
8(1)3,
8(2)6,
8(2)7,
9(2)5,
10(3)12,
10(3)13,
11(3)9,
12(1)1,
12(2)5,
12(3)9,
12(3)10,
13(1)2,
13(1)3,
13(1)4,
13(4)17
- treebank,
8(4)16,
9(2)6,
10(1)5,
10(3)12,
10(4)18,
11(3)9,
13(2)9
- Uchimoto, Kiyotaka,
4(1)18
- unlabeled,
12(2)7
- use,
4(2)159,
5(2)89,
5(2)146,
6(2)8,
6(3)11,
7(2)6,
7(3)9,
7(4)11,
7(4)12,
8(1)3,
8(2)9,
8(3)11,
9(1)1,
9(1)3,
9(3)11,
10(1)3,
10(1)4,
11(1)1,
11(2)6,
11(2)7,
11(3)8,
11(3)10,
11(4)14,
11(4)18,
12(1)1,
12(2)6,
12(3)9,
12(3)10,
13(2)6,
13(2)9,
13(2)10,
13(3)12
- used,
5(2)89,
5(2)146,
7(1)3,
7(2)6,
7(2)7,
7(3)9,
7(4)12,
7(4)13,
8(4)17,
9(1)1,
9(1)3,
9(2)6,
9(3)10,
10(1)2,
10(1)6,
10(2)7,
10(2)8,
10(3)12,
10(3)13,
10(4)20,
11(1)2,
11(1)3,
11(3)10,
11(4)13,
11(4)14,
12(2)5,
12(3)9,
12(3)11,
12(3)12,
13(2)6,
13(3)11
- which,
5(2)89,
5(2)121,
6(2)6,
6(2)8,
6(3)10,
6(4)1,
7(1)3,
7(2)7,
7(3)10,
7(4)13,
8(1)2,
8(1)4,
8(2)9,
8(3)12,
8(4)14,
8(4)16,
8(4)18,
9(1)1,
9(2)5,
9(3)12,
9(4)14,
9(4)15,
10(1)4,
10(1)6,
10(2)7,
10(2)8,
10(2)9,
10(3)12,
10(3)13,
10(3)14,
10(3)15,
10(4)17,
10(4)19,
10(4)20,
11(2)6,
11(3)8,
11(3)9,
11(4)13,
11(4)14,
11(4)15,
11(4)16,
11(4)18,
12(1)1,
12(1)3,
12(1)4,
12(2)5,
12(2)6,
12(2)7,
12(3)10,
12(3)11,
12(4)15,
12(4)17,
13(1)1,
13(2)8,
13(3)13,
13(4)17,
13(4)18