machine learning
Trí tuệ nhân tạo - Introduction to Machine Learning
... conform to newknowledge is impractical, but machine learning metho ds mightbeable to trackmuchofit.1.1.2 Wellsprings of Machine Learning Workinmachine learning is nowconverging from several sources. ... ers (1,0) or of categorical variablesIntroduction to Machine Learning c1996 Nils J. Nilsson. All rights reserved.INTRODUCTIONTO MACHINE LEARNING AN EARLY DRAFT OF A PROPOSEDTEXTBOOKNils ... eed-up learning with metho ds that create genuinely newfunctions|ones that might give dierent results after learning than theydid b efore. Wesay that the latter metho ds involve inductive learning. ...
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HỌC MÁY (MACHINE LEARNING)
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Tài liệu Machine Learning Multimedia Content Analysis ppt
... otherwise notified, the term machine learning will be used todenote inductive learning. During the early days of machine learning research, computer scientistsdeveloped learning algorithms based ... provides an overview of machine learning techniques andshows the strong relevance between typical multimedia content analysis and machine learning tasks. The overview of machine learning techniques ... havearoused people’s enthusiasms in machine learning, and have led to a spate ofnew machine learning text books. Noteworthily, among the ever growing listof machine learning books, many of them attempt...
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Tài liệu Báo cáo khoa học: "Extracting Comparative Sentences from Korean Text Documents Using Comparative Lexical Patterns and Machine Learning Techniques" doc
... AFNLPExtracting Comparative Sentences from Korean Text Documents Us-ing Comparative Lexical Patterns and Machine Learning Techniques Seon Yang Department of Computer Engineering, Dong-A University, 840 ... more elements of the keyword set is called a comparative-sentence candidate. Finally, we use machine learning techniques to eliminate non-comparative sentences from the candidates. As a result, ... non-comparative sen-tences from comparative sentence candidates with a CKL2 keyword, we employ machine learning techniques (MEM and Naïve Bayes). For feature extraction from each comparative-sentence...
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Tài liệu Báo cáo khoa học: "Trimming CFG Parse Trees for Sentence Compression Using Machine Learning Approaches" pptx
... to unsupervised learning to overcome thelack of training data. However their model alsohas the same problem. McDonald (McDonald,2006) independently proposed a new machine learning approach. ... Association for Computational LinguisticsTrimming CFG Parse Trees for Sentence Compression Using Machine Learning ApproachesYuya Unno1Takashi Ninomiya2Yusuke Miyao1Jun’ichi Tsujii1341Department ... former problem, we apply a maxi-mum entropy model to Knight and Marcu’s modelto introduce machine learning features that are de-fined not only for CFG rules but also for othercharacteristics...
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Tài liệu Báo cáo khoa học: "Machine Learning for Coreference Resolution: From Local Classification to Global Ranking" ppt
... pages 104–111.J. R. Quinlan. 1993. C4.5: Programs for Machine Learning. Morgan Kaufmann.W. M. Soon, H. T. Ng, and D. Lim. 2001. A machine learning approach to coreference resolution of nounphrases. ... selec-tion and error-driven pruning for machine learning ofcoreference rules. In Proc. of EMNLP, pages 55–62.V. Ng and C. Cardie. 2002b. Improving machine learn-ing approaches to coreference ... generate good can-didate partitions. Given that machine learning ap-proaches to the problem have been promising, ourchoices will be guided by previous learning- basedcoreference systems, as described...
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Machine Learning: A Probabilistic Perspective pptx
... 1}. Based on a figure by Leslie Kaelbling.1.2 Supervised learning We begin our investigation of machine learning by discussing supervised learning, which is theform of ML most widely used in practice.1.2.1 ... Cataloging-in-Publication InformationMurphy, Kevin P. Machine learning : a probabilistic perspective / Kevin P. Murphy.p. cm. — (Adaptive computation and machine learning series)Includes bibliographical ... Gaussian graphical models * 31810.3 Inference 31910.4 Learning 32010.4.1 Plate notation 32010.4.2 Learning from complete data 32210.4.3 Learning with missing and/or latent variables 32310.5...
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Báo cáo khoa học: Metabolomics, modelling and machine learning in systems biology – towards an understanding of the languages of cells potx
... Metabolomics, modelling and machine learning systemsFEBS Journal 273 (2006) 873–894 ª 2006 The Author Journal compilation ª 2006 FEBS 893profiling data using machine learning. Plant Physiol126, ... 110–117.52 Cohn DA, Atlas L & Ladner R (1994) Improving gen-eralisation with active learning. Machine Learning 15,201–221.53 Mackay D (1992) Information-based objective func-tions for active ... modelling and machine learning systemsFEBS Journal 273 (2006) 873–894 ª 2006 The Author Journal compilation ª 2006 FEBS 885337 Mackay DJC (2003) Information Theory, Inference and Learning Algorithms....
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Báo cáo khoa học: "Paraphrase Recognition Using Machine Learning to Combine Similarity Measures" ppt
... 27–35,Suntec, Singapore, 4 August 2009.c2009 ACL and AFNLPParaphrase Recognition Using Machine Learning to Combine SimilarityMeasuresProdromos MalakasiotisDepartment of InformaticsAthens ... correspondto machine translation evaluation metrics, ratherthan string similarity measures, unlike our system.We plan to examine further how the features ofFinch et al. and other ideas from machine ... INIT+WN+DEP uses ad-ditional features that measure grammatical rela-tion similarity. Supervised machine learning isused to learn how to combine the resulting fea-tures. We experimented with a Maximum...
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Báo cáo khoa học: "Using Machine-Learning to Assign Function Labels to Parser Output for Spanish" ppt
... LFG,Bergen, Norway.V. N. Vapnik. 1998. Statistical Learning Theory.Wiley-Interscience, September.143Figure 3: Processing architecture for the machine- learning- based method.duce the number of category ... three generic machine learning algorithms: a memory-based learner(Daelemans and van den Bosch, 2005), a maxi-mum entropy classifier (Berger et al., 1996) and aSupport Vector Machine classifier ... setting in the context of au-tomatically acquiring LFG resources for Spanishfrom Cast3LB. Machine- learning- based Cast3LBtag assignment yields statistically-significantlyimproved LFG f-structures...
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Báo cáo khoa học: "A Re-examination of Machine Learning Approaches for Sentence-Level MT Evaluation" ppt
... criteria. Machine learning af-fords a unified framework to compose these crite-ria into a single metric. In this paper, we havedemonstrated the viability of a regression approachto learning ... Linguistics.Simon Corston-Oliver, Michael Gamon, and Chris Brockett.2001. A machine learning approach to the automatic eval-uation of machine translation. In Proceedings of the 39thAnnual Meeting of ... studies suggest that machine learn-ing can be applied to develop good auto-matic evaluation metrics for machine trans-lated sentences. This paper further ana-lyzes aspects of learning that impact...
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Báo cáo khoa học: "Extraction of definitions using grammar-enhanced machine learning" pdf
... investigate whethercombining a basic grammar with machine learning can give better results than a sophisticated gram-mar combined with machine learning. Because thedatasets will be more imbalanced ... combination of a rule-basedgrammar and machine learning. We col-lected a Dutch text corpus containing 549definitions and applied a grammar on it. Machine learning was then applied to im-prove ... baseline grammars and machine learning classifiers. In Proceedings of the Sixth InternationalConference on Language Resources and Evaluation,LREC 2008.I. Fahmi and G. Bouma. 2006. Learning to iden-tify...
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Machine Learning for Hackers pot
... data used to build a machine learning process. The notion of observing data, learning from it, and thenautomating some process of recognition is at the heart of machine learning and formsthe ... exploring machine learning withR! Before we proceed to the case studies, however, we will review some R functionsand operations that we will use frequently.R Basics for Machine Learning As ... that they can think more clearly about the world in order to make betterdecisions.In machine learning, the learning occurs by extracting as much information from thedata as possible (or reasonable)...
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Natural Language Annotation for Machine Learning potx
... with machine learning algorithms that perform classification, clustering and pattern inductiontasks.• Having a good annotation scheme and accurate annotations are critical for machine learning ... you start fordesigning the features that go into your learning algorithm. The better the features, thebetter the performance of the machine learning algorithm!Preparing a corpus with annotations ... Entropy(Maxent), Naive Bayes, Decision trees, and Support Vector Machines (SVMs).ClusteringClustering is the name given to machine learning algorithms that find natural groupingsand patterns from...
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Automating the Construction of Internet Portals with Machine Learning doc
... forty: The independence assumption ininformation retrieval. In Machine Learning: ECML-98, Tenth EuropeanConference on Machine Learning, pp. 4–15.McCallum, A., & Nigam, K. (1998). A comparison ... 155–171.Mitchell, T. M. (1997). Machine Learning. McGraw-Hill, New York.cora.tex; 17/02/2000; 10:24; p.45Automating the Construction of Internet Portals with Machine Learning 9links to research ... dynamicprogramming.3.2. Spidering as Reinforcement Learning As an aid to understanding how reinforcement learning relates to spi-dering, consider the common reinforcement learning task of a mouseexploring...
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Báo cáo khoa học: "Machine-Learning-Based Transformation of Passive Japanese Sentences into Active by Separating Training Data into Each Input Particle" doc
... into Active Sen-tences Using Machine Learning, pages 115–125. SpringerPublisher.Masaki Murata, Qing Ma, and Hitoshi Isahara. 2002. Com-parison of three machine- learning methods for Thai part-of-speech ... using the machine- learning method ex-plained in Section 3. When multiple target parti-cles could have been answers in the training data,we used pairs of them as answers for machine learning. The ... separates training datainto each input particle and uses machine learning for each particle. We also usednumerous rich features for learning. Ourmethod obtained a high rate of accuracy(94.30%)....
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- machine learning in action
- using machine learning to maintain rulebased namedentity recognition
- a machine learning approach
- applying machine learning to chinese
- machine learning for coreference resolution
- machine learningbased coreference resolution of concepts in clinical documents
- machine learning for coreference resolution recent developments
- bootstrapping named entity recognition by means of active machine learning
- software for machine learning
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