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Modality prediction of biomedical literature images using multimodal feature representation ... : Klassifikation von Bildern der biomedizinischen Literatur unter Anwendung multimodaler Merkmale ...
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Exploration of Acoustic Features for Automatic Vowel Discrimination in Spontaneous Speech
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In: http://rave.ohiolink.edu/etdc/view?acc_num=osu1339695879 (2012)
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A Method for Stopping Active Learning Based on Stabilizing Predictions and the Need for User-Adjustable Stopping ...
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Taking into Account the Differences between Actively and Passively Acquired Data: The Case of Active Learning with Support Vector Machines for Imbalanced Datasets ...
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A Method for Stopping Active Learning Based on Stabilizing Predictions and the Need for User-Adjustable Stopping
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Taking into Account the Differences between Actively and Passively Acquired Data: The Case of Active Learning with Support Vector Machines for Imbalanced Datasets
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Language modeling for bag-of-visual words image categorization
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In: https://www.irisa.fr/texmex/people/claveau/publis/Tirilly_et_al_CIVR08.pdf (2008)
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Addressing Scalability Issues Of Named Entity Recognition Using Multi-Class Support Vector Machines ...
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Addressing Scalability Issues Of Named Entity Recognition Using Multi-Class Support Vector Machines ...
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Vowel Detection and Classification using Support Vector Machines (SVM)
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In: http://www.setit.rnu.tn/last_edition/setit2007/TI/99.pdf (2007)
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FIASCO: Filtering the Internet by automatic subtree classification, Osnabrück
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In: http://www.bcs.rochester.edu/people/jdegen/docs/BauerEtAl2007_FIASCO.pdf (2007)
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Abstract:
The FIASCO system implements a machine-learning approach for the automatic removal of boilerplate (navigation bars, link lists, page headers and footers, etc.) from Web pages in order to make them available as a clean and useful corpus for linguistic purposes. The system parses an HTML document into a DOM tree representation and identifies a set of disjoint subtrees that correspond to text blocks, headers or list items. Each block is then represented as a vector of linguistic, structural and visual features. A support vector machine classifier is used to distinguish between “clean ” and “dirty ” blocks. Dirty blocks are removed from the HTML tree before it is passed to the Lynx browser for conversion into plain text. The SVM classifier was trained and evaluated on a manually cleaned dataset of 158 English Web pages, the FIASCO gold standard.
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Keyword:
boilerplate; CLEANEVAL; machine learning; support vector machines; Web as corpus
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.552.4105 http://www.bcs.rochester.edu/people/jdegen/docs/BauerEtAl2007_FIASCO.pdf
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Content Classification of Multimedia Documents using Partitions of Low-Level Features ...
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Generative vs Discriminative Approaches to Entity Extraction from Label Deficient Data
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In: http://www.cavi.univ-paris3.fr/lexicometrica/jadt/jadt2004/pdf/JADT_049.pdf (2004)
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Tornado in Multilingual Opinion Analysis: A Transductive Learning Approach for Chinese Sentimental Polarity Recognition
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In: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings7/pdf/NTCIR7/C2/MOAT/18-NTCIR7-MOAT-WuY.pdf
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SVM BASED POSTERIOR PROBABILITIES FOR SYLLABLE CONFIDENCE ANNOTATION
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In: http://jth2008.ehu.es/cd/pdfs/articulo/art_64.pdf
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Robust Text Independent Speaker Identification Using Hybrid
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In: http://www.aicit.org/jdcta/ppl/jdcta_version10_Part14.pdf
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