A training algorithm for optimal margin classifiers
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The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
Experiments in multilingual information retrieval using the SPIDER system
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Cross-linguistic information retrieval workshop
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Generalized vector spaces model in information retrieval
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Making large-scale support vector machine learning practical
Advances in kernel methods
A re-examination of text categorization methods
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Natural language information retrieval: progress report
Information Processing and Management: an International Journal - The sixth text REtrieval conference (TREC-6)
AI Game Programming Wisdom
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Text classification using string kernels
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Two-stage statistical language models for text database selection
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Practical solutions to the problem of diagonal dominance in kernel document clustering
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Extracting key-substring-group features for text classification
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Convolution kernels with feature selection for natural language processing tasks
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Dependency-based sentence alignment for multiple document summarization
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Kernel-Based Learning of Hierarchical Multilabel Classification Models
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Weighted kernel model for text categorization
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Supervised automatic evaluation for summarization with voted regression model
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Kernel methods, syntax and semantics for relational text categorization
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A Graph-Based Approach for Sentiment Sentence Extraction
New Frontiers in Applied Data Mining
Neurocomputing
Psychiatric document retrieval using a discourse-aware model
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Discovering subword associations in strings in time linear in the output size
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A Quantitative Method for RSS Based Applications
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Fourier Domain Scoring with Document Structure Consideration
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Locality kernels for sequential data and their applications to parse ranking
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On a Kernel Regression Approach to Machine Translation
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Efficient linearization of tree kernel functions
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Coreference systems based on kernels methods
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Using lexical and relational similarity to classify semantic relations
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Syntactic Structural Kernels for Natural Language Interfaces to Databases
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Human activity encoding and recognition using low-level visual features
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Convolution kernels on constituent, dependency and sequential structures for relation extraction
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Classifier fusion for SVM-based multimedia semantic indexing
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On languages piecewise testable in the strict sense
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Using local alignments for relation recognition
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An effective approach for searching closest sentence translations from the web
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Information Processing and Management: an International Journal
Linguistic kernels for answer re-ranking in question answering systems
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A tree kernel-based method for protein-protein interaction mining from biomedical literature
KDLL'06 Proceedings of the 2006 international conference on Knowledge Discovery in Life Science Literature
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Using syntactic and semantic structural kernels for classifying definition questions in Jeopardy!
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Structured lexical similarity via convolution kernels on dependency trees
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A fast bit-parallel algorithm for gapped string kernels
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Combining classification with clustering for web person disambiguation
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Unsupervised modeling of dialog acts in asynchronous conversations
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Structural relationships for large-scale learning of answer re-ranking
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Verb classification using distributional similarity in syntactic and semantic structures
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Modeling topic dependencies in hierarchical text categorization
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
A weakly supervised model for sentence-level semantic orientation analysis with multiple experts
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Wikipedia-based WSD for multilingual frame annotation
Artificial Intelligence
Evaluating the impact of syntax and semantics on emotion recognition from text
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
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We address the problem of categorising documents using kernel-based methods such as Support Vector Machines. Since the work of Joachims (1998), there is ample experimental evidence that SVM using the standard word frequencies as features yield state-of-the-art performance on a number of benchmark problems. Recently, Lodhi et al. (2002) proposed the use of string kernels, a novel way of computing document similarity based of matching non-consecutive subsequences of characters. In this article, we propose the use of this technique with sequences of words rather than characters. This approach has several advantages, in particular it is more efficient computationally and it ties in closely with standard linguistic pre-processing techniques. We present some extensions to sequence kernels dealing with symbol-dependent and match-dependent decay factors, and present empirical evaluations of these extensions on the Reuters-21578 datasets.