Entry Che:2008:UHC from talip.bib
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BibTeX entry
@Article{Che:2008:UHC,
author = "Wanxiang Che and Min Zhang and AiTi Aw and ChewLim Tan
and Ting Liu and Sheng Li",
title = "Using a Hybrid Convolution Tree Kernel for Semantic
Role Labeling",
journal = j-TALIP,
volume = "7",
number = "4",
pages = "13:1--13:??",
month = nov,
year = "2008",
CODEN = "????",
DOI = "https://doi.org/10.1145/1450295.1450298",
ISSN = "1530-0226 (print), 1558-3430 (electronic)",
ISSN-L = "1530-0226",
bibdate = "Mon Dec 8 13:56:10 MST 2008",
bibsource = "http://portal.acm.org/;
http://www.math.utah.edu/pub/tex/bib/talip.bib",
abstract = "As a kind of Shallow Semantic Parsing, Semantic Role
Labeling (SRL) is gaining more attention as it benefits
a wide range of natural language processing
applications. Given a sentence, the task of SRL is to
recognize semantic arguments (roles) for each predicate
(target verb or noun). Feature-based methods have
achieved much success in SRL and are regarded as the
state-of-the-art methods for SRL. However, these
methods are less effective in modeling structured
features. As an extension of feature-based methods,
kernel-based methods are able to capture structured
features more efficiently in a much higher dimension.
Application of kernel methods to SRL has been achieved
by selecting the tree portion of a predicate and one of
its arguments as feature space, which is named as
predicate-argument feature (PAF) kernel. The PAF kernel
captures the syntactic tree structure features using
convolution tree kernel, however, it does not
distinguish between the path structure and the
constituent structure. In this article, a hybrid
convolution tree kernel is proposed to model different
linguistic objects. The hybrid convolution tree kernel
consists of two individual convolution tree kernels.
They are a Path kernel, which captures
predicate-argument link features, and a Constituent
Structure kernel, which captures the syntactic
structure features of arguments. Evaluations on the
data sets of the CoNLL-2005 SRL shared task and the
Chinese PropBank (CPB) show that our proposed hybrid
convolution tree kernel statistically significantly
outperforms the previous tree kernels. Moreover, in
order to maximize the system performance, we present a
composite kernel through combining our hybrid
convolution tree kernel method with a feature-based
method extended by the polynomial kernel. The
experimental results show that the composite kernel
achieves better performance than each of the individual
methods and outperforms the best reported system on the
CoNLL-2005 corpus when only one syntactic parser is
used and on the CPB corpus when automated syntactic
parse results and correct syntactic parse results are
used respectively.",
acknowledgement = ack-nhfb,
articleno = "13",
fjournal = "ACM Transactions on Asian Language Information
Processing",
journal-URL = "http://portal.acm.org/browse_dl.cfm?&idx=J820",
keywords = "hybrid convolution tree kernel; semantic role
labeling",
}
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13(1)2,
13(3)11,
13(3)12
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10(3)15,
11(2)7,
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11(4)14,
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13(3)13,
13(4)17
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- parsing,
1(2)123,
2(4)301,
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12(4)17
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9(2)5,
9(2)6,
9(3)11,
9(3)12,
9(4)14,
10(2)8,
10(3)13,
10(3)14,
11(2)7,
11(3)10,
11(3)11,
11(4)14,
11(4)15,
11(4)17,
12(1)2,
12(3)9,
12(3)11,
12(4)14,
12(4)15,
12(4)16,
13(1)3,
13(1)4,
13(2)7,
13(2)9,
13(4)16,
13(4)17
- portion,
8(3)11,
11(2)7
- predicate,
10(3)13,
12(3)11
- predicate-argument,
11(4)16
- present,
5(2)89,
5(2)165,
6(2)7,
6(3)10,
6(4)2,
7(1)2,
7(1)3,
7(2)7,
7(3)9,
7(4)11,
8(1)3,
8(2)6,
8(2)7,
8(2)8,
8(3)10,
8(4)14,
8(4)16,
8(4)17,
8(4)18,
8(4)19,
9(1)1,
9(1)2,
9(1)3,
9(2)6,
9(4)14,
10(1)4,
10(1)6,
10(2)7,
10(3)14,
10(4)18,
10(4)19,
11(1)2,
11(1)3,
11(2)4,
11(2)5,
11(2)6,
11(3)10,
11(4)13,
12(1)3,
12(2)5,
12(3)9,
12(3)11,
12(4)15,
13(2)8,
13(4)16
- previous,
5(2)89,
5(2)121,
7(2)7,
9(2)5,
10(3)15,
10(4)18,
11(2)6,
13(2)6,
13(3)12,
13(4)18
- processing,
3(1)1,
3(4)213,
4(4)375,
5(2)121,
5(4)291,
6(2)7,
6(3)9,
6(3)10,
6(4)3,
7(1)1,
7(1)3,
7(2)7,
8(1)2,
8(2)9,
8(4)13,
8(4)14,
8(4)16,
8(4)18,
8(4)19,
9(2)5,
9(2)6,
9(3)11,
9(4)15,
10(3)11,
10(3)14,
10(4)20,
11(1)2,
11(3)9,
11(4)15,
12(1)3,
12(3)10,
13(1)1,
13(2)7
- proposed,
5(2)121,
5(2)165,
6(2)7,
7(1)1,
7(1)2,
7(3)9,
7(3)10,
7(4)11,
8(1)4,
8(2)6,
8(3)10,
8(3)11,
8(4)14,
8(4)19,
9(1)1,
9(2)5,
9(2)7,
10(2)7,
10(2)9,
10(3)14,
10(4)18,
11(1)3,
11(2)5,
11(2)6,
11(2)7,
11(3)8,
11(3)9,
11(3)10,
11(3)11,
11(4)16,
11(4)17,
12(1)4,
12(2)5,
12(2)7,
12(3)12,
12(4)16,
12(4)17,
13(2)6,
13(2)8,
13(3)13,
13(4)18
- range,
7(4)11,
9(2)6
- recognize,
11(3)11,
11(4)14,
11(4)15,
12(1)3,
12(3)10
- regarded,
11(4)13
- reported,
11(1)1,
11(1)2,
11(2)7,
13(1)4,
13(2)6,
13(3)14
- respectively,
7(4)11,
10(3)12,
10(3)13,
12(1)1,
12(1)4,
13(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,
8(1)2,
8(1)3,
8(1)4,
8(2)6,
8(2)9,
8(3)10,
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
- role,
5(3)228,
8(2)8,
9(4)13,
10(3)13,
11(4)18,
12(3)11
- selecting,
9(3)12
- semantic,
3(1)66,
3(2)94,
5(2)165,
5(3)228,
7(1)2,
7(1)3,
8(1)2,
8(2)6,
8(3)12,
8(4)15,
9(2)7,
10(1)5,
10(3)13,
10(3)14,
10(3)15,
10(4)20,
10(4)21,
11(3)8,
11(3)11,
11(4)15,
11(4)18,
12(3)11,
12(4)16
- sentence,
1(3)173,
3(2)146,
4(3)321,
4(4)377,
5(2)121,
5(2)146,
5(2)165,
7(1)3,
7(2)6,
8(1)3,
8(2)8,
9(1)2,
9(2)6,
10(4)21,
11(1)3,
11(2)5,
11(2)6,
11(3)8,
11(3)10,
11(3)11,
12(1)2,
12(1)3,
12(2)7,
12(4)14,
12(4)17,
13(1)2,
13(3)11,
13(4)17
- set,
1(3)269,
5(2)121,
6(1)z,
7(1)3,
7(3)8,
7(4)11,
8(3)10,
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
- shallow,
9(4)15,
13(2)9
- shared,
12(4)16
- show,
5(2)89,
5(2)146,
7(1)1,
7(1)2,
7(1)3,
7(4)11,
7(4)12,
8(1)4,
8(2)7,
8(2)9,
8(3)12,
8(4)16,
8(4)17,
9(1)1,
9(1)2,
9(1)3,
9(2)5,
9(2)6,
9(2)7,
9(3)11,
9(3)12,
9(4)14,
10(1)3,
10(3)15,
11(2)4,
11(2)5,
11(2)7,
11(3)8,
11(3)11,
11(4)14,
11(4)15,
11(4)17,
11(4)18,
12(1)2,
12(1)4,
12(2)5,
12(2)7,
12(3)9,
12(3)10,
12(3)11,
12(4)15,
12(4)16,
13(1)3,
13(2)6,
13(2)7,
13(2)9,
13(3)14
- significantly,
7(1)1,
8(2)6,
8(4)15,
8(4)18,
9(1)2,
9(2)6,
9(3)12,
11(2)6,
11(4)13,
11(4)17,
12(4)16,
13(2)6,
13(4)17
- space,
6(2)6,
6(2)7,
11(2)5,
11(3)9
- SRL,
10(3)13
- state-of-the-art,
6(4)1,
6(4)3,
7(2)7,
7(4)12,
8(1)4,
8(2)6,
8(2)7,
9(2)5,
11(1)1,
11(3)8,
11(4)15,
12(1)1,
12(4)14,
12(4)16,
13(3)13
- statistically,
8(4)16,
9(3)11,
11(2)6
- structure,
4(2)186,
5(2)89,
7(1)1,
7(3)8,
8(1)2,
8(1)4,
8(4)19,
10(3)12,
10(3)14,
11(3)8,
11(4)16,
12(1)3,
12(4)17
- structured,
12(3)10
- success,
7(4)12
- syntactic,
6(4)1,
7(2)6,
7(4)12,
8(1)4,
8(4)15,
9(2)6,
10(3)12,
10(3)15,
10(4)17,
11(3)8,
11(4)14,
11(4)15,
11(4)18,
12(4)17,
13(2)9
- target,
5(2)121,
6(4)1,
8(1)3,
8(2)7,
8(2)8,
8(3)12,
8(4)17,
9(1)1,
10(3)12,
10(4)17,
11(4)17,
12(2)7,
12(3)11,
12(3)12
- task,
2(1)49,
5(2)89,
5(2)121,
6(2)7,
6(3)11,
6(4)1,
6(4)3,
7(1)1,
7(1)2,
7(2)7,
7(3)10,
8(1)4,
8(2)7,
8(4)15,
8(4)16,
9(1)4,
9(2)6,
9(3)10,
9(4)14,
9(4)15,
10(1)5,
10(3)14,
10(4)18,
10(4)20,
10(4)21,
11(1)2,
11(3)8,
11(3)11,
11(4)13,
11(4)14,
11(4)17,
11(4)18,
12(1)2,
12(1)3,
12(2)5,
12(2)7,
12(3)9,
12(4)17,
13(2)10,
13(4)17
- than,
5(2)146,
6(3)10,
7(3)8,
7(4)11,
8(2)8,
8(4)16,
9(1)2,
9(2)7,
9(3)11,
9(3)12,
10(1)3,
10(1)4,
10(3)14,
11(2)4,
11(2)7,
11(3)8,
11(3)9,
11(4)13,
11(4)15,
12(2)7,
12(3)10,
12(4)16,
13(1)1,
13(4)17
- the-art, state-of-,
6(4)1,
6(4)3,
7(2)7,
7(4)12,
8(1)4,
8(2)7,
9(2)5,
11(1)1,
11(3)8,
11(4)15,
12(1)1,
12(4)14,
12(4)16,
13(3)13
- through,
6(4)2,
8(2)9,
9(3)11,
10(3)12,
11(2)4,
11(3)10,
13(1)3
- tree,
10(3)12,
10(3)15,
10(4)18,
11(2)6
- two,
5(2)89,
7(2)7,
7(3)8,
7(4)11,
7(4)12,
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)1,
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
- used,
5(2)89,
5(2)146,
7(1)3,
7(2)6,
7(2)7,
7(3)9,
7(4)12,
8(3)10,
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
- verb,
4(1)18
- when,
5(2)89,
6(3)9,
6(3)11,
7(2)6,
7(4)11,
8(1)3,
8(4)16,
8(4)17,
9(1)3,
9(2)5,
9(3)11,
9(3)12,
9(4)13,
11(2)4,
12(1)2,
12(4)14,
13(2)8,
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,
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)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
- wide,
9(1)1
- Zhang, Min,
8(1)4