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Determining the Dependency Among Clauses Based on Machine Learning Techniques.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Rangan, C. Pandu
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Beliczynski, Bartlomiej
Dzielinski, Andrzej
Iwanowski, Marcin
Ribeiro, Bernardete
Kim, Mi-Young
Source :
Adaptive & Natural Computing Algorithms (9783540715894); 2007, p814-821, 8p
Publication Year :
2007

Abstract

The longer the input sentences, the worse the syntactic parsing results. Therefore, a long sentence is first divided into several clauses, and syntactic analysis for each clause is performed. Finally, all the analysis results are merged into one. In the merging process, it is difficult to determine the dependency among clauses. To handle such syntactic ambiguity among clauses, this paper proposes two-step clause-dependency determination method based on machine learning techniques. We extract various clause-specific features, and analyze the effect of each feature on the performance. For the Korean texts, we experiment using four kinds of machine-learning methods. Logitboosting method performed best and it also outperformed the previous rule-based methods. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540715894
Database :
Complementary Index
Journal :
Adaptive & Natural Computing Algorithms (9783540715894)
Publication Type :
Book
Accession number :
33109872
Full Text :
https://doi.org/10.1007/978-3-540-71618-1_91