[PDF] Top 20 Identifying Metaphorical Word Use with Tree Kernels
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Identifying Metaphorical Word Use with Tree Kernels
... etc. Identifying metaphors is thus an important step in lan- guage ...any word can serve as a metaphor, they are impossible to ...identify metaphorical use, we assume that it results in ... See full document
6
Open Information Extraction with Tree Kernels
... dependency tree kernel model (Moschitti, 2006) for both ...parse tree for semantic tasks is difficult. SVM tree kernels avoid extracting explicit features from parse trees by calculating the ... See full document
10
Towards Compositional Tree Kernels
... the Tree Ker- nels operators, a co-occurrence Word Space is ac- quired through the distributional analysis of the UkWaC corpus (Baroni et ...co-occurrence Word- Space with a window of size 3 is ... See full document
9
Exploring Syntactic Structural Features for Sub Tree Alignment Using Bilingual Tree Kernels
... The word segmentation, toke- nization and parse-tree in the corpus are manually constructed or ...in word align- ...parse tree, designed by the annotator, is em- ...We use 5000 ... See full document
10
Dependency Tree Kernels for Relation Extraction
... dependency tree ker- nel for relation extraction provides a vast improve- ment over a bag-of-words ...pendency tree kernel appears to perform well at the task of classifying relations, recall is still ... See full document
7
Exploiting CCG Structures with Tree Kernels for Speculation Detection
... by tree kernels is more useful when disambiguating speculative key- words than ...The use of tree kernels needs further investigations in order to evaluate the suitability of this ... See full document
6
Recognising Sets and Their Elements: Tree Kernels for Entity Instantiation Identification
... Theoretical linguistic literature has discussed set membership and subset bridging (Clark, 1975; Prince, 1981), and the phenomenon has been annotated in at least three corpora (Poesio, 2003; Nissim et al., 2004; Markert ... See full document
11
Convolution Kernels for Opinion Holder Extraction
... convolution kernels, such as sequence and tree ker- nels, are quite effective when compared to manual feature engineering (Moschitti, 2008; Bunescu and Mooney, 2005; Nguyen et ...effectively use ... See full document
9
Domain Kernels for Word Sense Disambiguation
... the use of Domain Models allows us to reduce the amount of training data, opening an interesting research di- rection for all those NLP tasks for which the Knowl- edge Acquisition Bottleneck is a crucial ...a ... See full document
8
Convolutional Sentence Kernel from Word Embeddings for Short Text Categorization
... first tree kernels to compare trees based on their topology ...Dependency Tree Kernels (DTK) to capture syntactic similar- ities while Bloehdorn and Moschitti (2007) and Croce et ...Syntactic ... See full document
6
Speeding up Training with Tree Kernels for Node Relation Labeling
... the tree structure, we used the output of Collins’ parser (with WSJ- style non-terminals) provided with the data ...the word nodes. The average num- ber of nodes in a tree was about ...the ... See full document
8
Detecting Opinion Polarities using Kernel Methods
... any-gram kernels, which not only avoids this expense, but also models all orders of n-grams in a ...binary tree in such a way that all possible n-grams are captured by valid tree fragments, which are ... See full document
10
Modelling input texts: from Tree Kernels to Deep Learning
... we use 100k examples from the second section of the SRL ...same tree kernel), it is the number of ∆ calls (see ...PTK kernels and used uSVM outcome as a ... See full document
199
Going beyond sentences when applying tree kernels
... parse tree kernels to ...sentence kernels with the ones for extended parse trees and show that adding discourse information to learning data helps to improve classifica- tion ... See full document
8
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 ... See full document
10
Exploiting graph kernels for high performance biomedical relation extraction
... In ASM kernel, edge labels (dependency types D) and node labels (word lemmas V ) are treated separately. ASM associates a node label pair with a rich feature vector, where each feature is a function of the edge ... See full document
11
Automated essay scoring with string kernels and word embeddings
... Bag-of-super-word-embeddings. Word embed- dings are long known in the NLP community (Bengio et ...the word embed- dings, Butnaru and Ionescu (2017) developed an approach termed ... See full document
7
Domestication and improvement of tropical crops for multi-functional farming systems
... largest kernels were found in many different populations and so were not closely related (Figure ...large kernels but they will be genetically diverse in all the unselected traits, such as pest and disease ... See full document
23
Making Tree Kernels Practical for Natural Language Learning
... that tree kernels can effectively be adopted in practical natural lan- guage ...their use are their efficiency and accuracy lower than traditional feature based ...ate tree kernels in a ... See full document
8
Statistical Metaphor Processing
... Both Birke and Sarkar (2006) and Gedigian et al. (2006) focus only on metaphors expressed by a verb. The approach of Krishnakumaran and Zhu (2007) additionally covers metaphors expressed by nouns and adjectives. ... See full document
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