tree kernels
Approximate Tree Kernels
... trees kernels with SVMs as underlying learning algorithms for question classification, web spam detection and intrusion ...imate tree kernels not only replicate the predictive performances of exact ...
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Using Tree Kernels for Classifying Temporal Relations between Events
... With recent construction of the Timebank corpus (Pustejovsky et al, 2003), the efficiency of different machine learning methods can now be compared. The recent work with Timebank has disclosed that six-class ...
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Frame Semantic Tree Kernels for Social Network Extraction from Text
... add tree kernel representations and features derived from frame-semantic parses to our previously proposed ...trast, tree kernels are able to find and leverage less strict patterns without requiring ...
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Embedding Semantic Similarity in Tree Kernels for Domain Adaptation of Relation Extraction
... tion tree kernels embedding lexical semantic sim- ...exploits kernels, structures and similarities for do- main ...of tree fragments generalized at the lexical level provides an effective ...
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The Impact of Modeling Overall Argumentation with Tree Kernels
... Several approaches have been proposed to model either the explicit sequential struc- ture of an argumentative text or its implicit hierarchical structure. So far, the adequacy of these models of overall argumentation ...
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Identifying Metaphorical Word Use with Tree Kernels
... A metaphor is a figure of speech that refers to one concept in terms of another, as in “He is such a sweet person”. Metaphors are ubiq- uitous and they present NLP with a range of challenges for WSD, IE, etc. Identifying ...
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Tree Kernels for Machine Translation Quality Estimation
... parse tree information in our Machine Learning (ML) component, we used tree kernel ...functions. Tree kernels (Collins and Duffy, 2001) are kernel functions defined over pairs of tree ...
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Exploiting CCG Structures with Tree Kernels for Speculation Detection
... by tree kernels is more useful when disambiguating speculative key- words than ...of tree kernels needs further investigations in order to evaluate the suitability of this ...
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Speeding up Training with Tree Kernels for Node Relation Labeling
... using tree ker- nels and other convolution kernels tends to overfit and propose selecting or restricting features (Cumby and Roth, 2003; Suzuki et ...full tree kernels for ...
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Making Tree Kernels Practical for Natural Language Learning
... which tree fragments may have been useful for semantic role labeling was not an easy ...possible tree subparts. This is exactly what the tree kernels can automatically do: the designer just ...
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Discriminative Reranking of Discourse Parses Using Tree Kernels
... Reranking models can make the global struc- tural information available to the system as fol- lows: first, a base parser produces several DT hypotheses; and then a classifier exploits the en- tire information in each ...
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Recognising Sets and Their Elements: Tree Kernels for Entity Instantiation Identification
... of tree kernels to the detection of both intra- and intersentential entity ...use tree kernels to learn directly from constituency parse tree ...Our tree kernels perform ...
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Going beyond sentences when applying tree kernels
... ‒ tree kernels built over syntactic parse trees. Convolution tree kernel (Collins and Duffy, 2002) defines a feature space consisting of all subtree types of parse trees and counts the number of ...
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Exploring Syntactic Structural Features for Sub Tree Alignment Using Bilingual Tree Kernels
... Bilingual Tree Kernels (BTKs) to capture the structural similarities across a pair of syntactic translational equivalences and apply BTKs to sub-tree alignment along with some plain ...parse ...
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Sentence Similarity based on Dependency Tree Kernels for Multi document Summarization
... dependency tree based sentence similarity kernels, which have originally been proposed for relation ...dependency tree based kernels DTK and Tri-K out- performed bag of words based ...
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Open Information Extraction with Tree Kernels
... Traditional relation extraction seeks to iden- tify pre-specified semantic relations within natural language text, while open Information Extraction (Open IE) takes a more general ap- proach, and looks for a variety of ...
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On the Effectiveness of Using Syntactic and Shallow Semantic Tree Kernels for Automatic Assessment of Essays
... semantic tree kernels for the task of automatic essay grading to improve the basic LSA model’s ...aggregated tree kernel scores of all possible sentence ...
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Towards Compositional Tree Kernels
... ticular, Tree Kernels (TKs) introduced in (Collins and Duffy, 2001), are largely used in NLP for their ability in capturing text grammatical information, directly from syntactic parse ...
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Argumentative Evidences Classification and Argument Scheme Detection Using Tree Kernels
... This work presents an approach for classifying evidence typology within arguments using Tree Kernels (TKs, described in Moschitti, 2006) with the aim to facilitate the detection of Argument Schemes. TKs ...
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A Study on Dependency Tree Kernels for Automatic Extraction of Protein Protein Interaction
... of tree kernels is the dependency tree (DT) kernel (Culotta and Sorensen, 2004; Nguyen et ...a tree kernel that is computed on a dependency tree (or ...dependency tree encodes ...
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