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19
Tree kernels for semantic role labeling
- Computational Linguistics
, 2008
"... The availability of large scale data sets of manually annotated predicate–argument structures has recently favored the use of machine learning approaches to the design of automated semantic role labeling (SRL) systems. The main research in this area relates to the design choices for feature represen ..."
Abstract
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Cited by 60 (14 self)
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in kernelbased machines, for example, perceptrons or support vector machines. In particular, we define different kinds of tree kernels as general approaches to feature engineering in SRL. Moreover, we extensively experiment with such kernels to investigate their contribution to individual stages of an SRL
Glycan classification with tree kernels
, 2007
"... Motivation: Glycans are covalent assemblies of sugar that play crucial roles in many cellular processes. Recently, comprehensive data about the structure and function of glycans have been accumulated, therefore the need for methods and algorithms to analyze these data is growing fast. Results: This ..."
Abstract
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Cited by 5 (0 self)
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: This article presents novel methods for classifying glycans and detecting discriminative glycan motifs with support vector machines (SVM). We propose a new class of tree kernels to measure the similarity between glycans. These kernels are based on the comparison of tree substructures, and take into account
Semantic convolution kernels over dependency trees: smoothed partial tree kernel
- In CIKM
, 2011
"... In recent years, natural language processing techniques have been used more and more in IR. Among other syntactic and semantic parsing are effective methods for the design of complex applica-tions like for example question answering and sentiment analy-sis. Unfortunately, extracting feature represen ..."
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Cited by 3 (1 self)
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representations suitable for machine learning algorithms from linguistic structures is typically difficult. In this paper, we describe one of the most advanced piece of technology for automatic engineering of syntactic and se-mantic patterns. This method merges together convolution depen-dency tree kernels
unknown title
"... Detection and Characterization (ACE RDC) corpora shows that the proposed tree kernel-based method outperforms other state-of-the-art methods. rtant ents Mes Much research has been performed on the extraction of semantic relations between named entities. Feature vector-based methods [8,10,24–28] reca ..."
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Detection and Characterization (ACE RDC) corpora shows that the proposed tree kernel-based method outperforms other state-of-the-art methods. rtant ents Mes Much research has been performed on the extraction of semantic relations between named entities. Feature vector-based methods [8
unknown title
"... Application of latent semantic analysis to protein remote homology detection Qi-wen Dong*, Xiao-long Wang, Lei Lin Motivation: Remote homology detection between protein sequences is a central problem in computational biology. The discriminative method such as the Support Vector Machine (SVM) is one ..."
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of most effective methods. Many of SVM-based methods focus on finding useful representations of protein sequence, using either explicit feature vector representations or kernel functions. Such representations may suffer from the peaking phenomenon in many machinelearning methods because the features
Automatic Annotation of Planetary Surfaces with Geomorphic Labels
- IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
, 2010
"... We present a methodology for automatic geomorphic mapping of planetary surfaces that incorporates machine learning techniques. Our application transforms remotely sensed topographic data gathered by orbiting satellites into semantically meaningful maps of landforms; such maps are valuable research ..."
Abstract
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Cited by 2 (0 self)
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and classification components. The segmentation assessment includes K-means based agglomerative segmentation and watershed-based segmentation. The classification assessment includes three supervised learning algorithms: Naive Bayes, Bagging with decision trees, and Support Vector Machines (SVM); segments
and
, 2015
"... Effective support for custom proof automation is essential for large-scale interactive proof develop-ment. However, existing languages for automation via tactics either (a) provide no way to specify the behavior of tactics within the base logic of the accompanying theorem prover, or (b) rely on adva ..."
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on advanced type-theoretic machinery that is not easily integrated into established theorem provers. We present Mtac, a lightweight but powerful extension to Coq that supports dependently typed tactic programming. Mtac tactics have access to all the features of ordinary Coq programming, as well as a new set
Building multiclass classifiers for remote homology detection and fold recognition
- BMC Bioinformatics
"... Abstract Background: Protein remote homology detection and fold recognition are central problems in computational biology. Supervised learning algorithms based on support vector machines are currently one of the most effective methods for solving these problems. These methods are primarily used to ..."
Abstract
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Cited by 10 (6 self)
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algorithms based on support vector machines are currently one of the most effective methods for remote homology detection. The performance of these methods depends on how the protein sequences are modeled and on the method used to compute the kernel function between them. Availability and Requirements
Saskatoon By
"... In presenting this thesis in partial fulfilment of the requirements for a Postgraduate degree ..."
Abstract
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In presenting this thesis in partial fulfilment of the requirements for a Postgraduate degree
SIMULATION, DEVELOPMENT AND DEPLOYMENT OF MOBILE WIRELESS SENSOR NETWORKS FOR MIGRATORY BIRD TRACKING
, 2012
"... This thesis presents CraneTracker, a multi-modal sensing and communication system for monitoring migratory species at the continental level. By exploiting the robust and extensive cellular infrastructure across the continent, traditional mobile wireless sensor networks can be extended to enable reli ..."
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This thesis presents CraneTracker, a multi-modal sensing and communication system for monitoring migratory species at the continental level. By exploiting the robust and extensive cellular infrastructure across the continent, traditional mobile wireless sensor networks can be extended to enable reliable, low-cost monitoring of migratory species. The developed multi-tier architecture yields ecologists with unconventional behavior in-formation not furnished by alternative tracking systems at such a large scale and for a low-cost. The simulation, development and implementation of the CraneTracker soft-ware system is presented. The system is shown effective through multiple proxy deploy-
Results 1 - 10
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19