Entry Hao:2013:TPP from talip.bib
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BibTeX entry
@Article{Hao:2013:TPP,
author = "Tianyong Hao and Chunshen Zhu",
title = "Toward a Professional Platform for {Chinese} Character
Conversion",
journal = j-TALIP,
volume = "12",
number = "1",
pages = "1:1--1:??",
month = mar,
year = "2013",
CODEN = "????",
DOI = "https://doi.org/10.1145/2425327.2425328",
ISSN = "1530-0226 (print), 1558-3430 (electronic)",
ISSN-L = "1530-0226",
bibdate = "Sat Mar 2 09:25:42 MST 2013",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/talip.bib",
abstract = "Increasing communication among Chinese-speaking
regions using respectively traditional and simplified
Chinese character systems has highlighted the
subtle-yet-extensive differences between the two
systems, which can lead to unexpected hindrance in
converting characters from one to the other. This
article proposes a new priority-based multi-data
resources management model, with a new algorithm called
Fused Conversion algorithm from Multi-Data resources
(FCMD), to ensure more context-sensitive, human
controllable, and thus more reliable conversions, by
drawing on reverse maximum matching, n -gram-based
statistical model and pattern-based learning and
matching. After parameter training on the Tagged
Chinese Gigaword corpus, its conversion precision
reaches 91.5\% in context-sensitive cases, the most
difficult part in the conversion, with an overall
precision rate at 99.8\%, a significant improvement
over the state-of-the-art models. The conversion
platform based on the model has extra features such as
data resource selection and $n$-grams self-learning
ability, providing a more sophisticated tool good
especially for high-end professional uses.",
acknowledgement = ack-nhfb,
articleno = "1",
fjournal = "ACM Transactions on Asian Language Information
Processing",
journal-URL = "http://portal.acm.org/browse_dl.cfm?&idx=J820",
}
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6(2)6,
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7(3)8,
7(3)9,
7(4)11,
7(4)13,
8(2)9,
8(4)16,
8(4)17,
9(1)1,
9(2)5,
9(2)7,
9(3)12,
9(4)14,
10(1)5,
10(3)12,
10(3)13,
10(4)19,
11(2)4,
11(2)6,
11(2)7,
11(4)14,
12(1)2,
12(2)5,
12(2)7,
12(3)11,
12(4)16,
13(1)4,
13(2)10,
13(4)17,
13(4)18
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5(2)165,
7(2)6,
7(2)7,
7(3)8,
7(4)11,
8(1)2,
8(2)7,
8(4)14,
8(4)16,
8(4)17,
9(1)1,
10(2)7,
10(4)20,
11(2)4,
11(2)7,
11(4)18,
12(1)3,
12(3)11,
12(4)16,
13(1)3,
13(1)4,
13(2)7
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6(4)1,
12(4)14
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12(3)9
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8(4)17,
8(4)18,
8(4)19,
9(3)9,
12(1)3,
12(1)4,
12(3)9,
12(3)10,
13(4)18
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7(2)5
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12(1)2
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7(3)9,
9(3)11,
10(2)8,
11(3)11,
11(4)18,
13(2)6
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5(2)89,
6(2)6,
6(2)8,
6(3)11,
7(3)8,
7(3)10,
7(4)12,
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13(2)8,
13(2)9,
13(3)12,
13(3)13,
13(4)17,
13(4)18
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12(3)11,
13(2)7
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6(3)9,
7(1)2,
7(3)10,
10(1)2,
10(1)6,
10(2)7,
12(1)4,
13(2)8
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13(1)4
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13(2)7
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8(1)3,
12(2)7,
13(1)3
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2(2)101,
2(2)124,
4(2)135,
5(2)89,
7(3)9,
7(4)11,
8(2)9,
8(3)12,
8(4)17,
9(2)5,
9(3)12,
9(4)14,
10(2)8,
10(3)12,
10(3)16,
10(4)19,
11(4)14,
11(4)16,
11(4)18,
12(4)14,
12(4)16,
13(1)1,
13(1)3,
13(2)7
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7(4)11,
7(4)13,
10(3)12,
10(3)13,
12(1)4,
13(3)14
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12(3)12
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1(1)34,
7(1)3,
8(1)3,
8(2)8,
8(4)15,
8(4)19,
9(2)5,
9(3)12,
13(3)13
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5(2)121,
7(1)3,
8(1)4,
8(4)15,
8(4)16,
8(4)17,
8(4)18,
9(2)5,
9(3)11,
10(1)5,
10(2)8,
10(3)14,
11(2)6,
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12(4)16,
13(1)3,
13(3)14,
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7(4)11,
12(3)11,
12(4)16
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7(4)12,
9(4)15
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6(4)1,
6(4)3,
7(2)7,
7(4)12,
7(4)13,
8(1)4,
8(2)6,
8(2)7,
9(2)5,
11(1)1,
11(3)8,
11(4)15,
12(4)14,
12(4)16,
13(3)13
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1(1)3,
3(2)87,
3(4)243,
5(2)121,
5(4)323,
5(4)360,
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7(1)1,
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8(1)4,
8(2)6,
8(2)7,
8(2)8,
8(2)9,
8(3)10,
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(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)10,
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)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
- the-art, state-of-,
6(4)1,
6(4)3,
7(2)7,
7(4)12,
7(4)13,
8(1)4,
8(2)7,
9(2)5,
11(1)1,
11(3)8,
11(4)15,
12(4)14,
12(4)16,
13(3)13
- thus,
6(2)6,
7(4)11,
9(2)7,
10(2)9,
12(4)15
- tool,
6(2)7
- toward,
1(1)3,
4(2)78,
6(3)10,
8(4)18,
11(2)5,
13(2)7
- traditional,
5(2)121,
6(2)7,
7(4)11,
8(2)6,
12(4)16
- training,
5(2)121,
6(3)11,
7(1)1,
8(1)3,
8(2)6,
8(2)7,
8(3)10,
9(2)5,
10(3)12,
10(3)13,
11(3)9,
12(2)5,
12(3)9,
12(3)10,
13(1)2,
13(1)3,
13(1)4,
13(4)17
- two,
5(2)89,
7(2)7,
7(3)8,
7(4)11,
7(4)12,
7(4)13,
8(1)4,
8(2)7,
8(4)17,
9(1)2,
9(3)11,
9(4)13,
10(1)2,
10(3)12,
10(3)14,
10(3)15,
10(4)20,
11(2)4,
11(2)5,
11(2)7,
11(3)8,
11(3)9,
11(3)11,
11(4)17,
12(1)2,
12(1)4,
12(2)5,
12(3)10,
12(3)11,
12(4)16,
13(1)1,
13(1)3,
13(1)4,
13(2)6,
13(2)9,
13(3)11,
13(4)17
- 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)10,
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(2)6,
12(3)9,
12(3)10,
13(2)6,
13(2)9,
13(2)10,
13(3)12
- 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)10,
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)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