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020 _a9783642051791
_9978-3-642-05179-1
040 _cMX-MeUAM
050 4 _aQ342
082 0 4 _a006.3
_223
100 1 _aKoronacki, Jacek.
_eeditor.
245 1 0 _aAdvances in Machine Learning II
_h[recurso electrónico] :
_bDedicated to the Memory of Professor Ryszard S.Michalski /
_cedited by Jacek Koronacki, Zbigniew W. Ras, Slawomir T. Wierzchon, Janusz Kacprzyk.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2010.
300 _aXIX, 531 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-949X ;
_v263
505 0 _aGeneral Issues -- Knowledge-Oriented and Distributed Unsupervised Learning for Concept Elicitation -- Toward Interactive Computations: A Rough-Granular Approach -- Data Privacy: From Technology to Economics -- Adapting to Human Gamers Using Coevolution -- Wisdom of Crowds in the Prisoner’s Dilemma Context -- Logical and Relational Learning, and Beyond -- Towards Multistrategic Statistical Relational Learning -- About Knowledge and Inference in Logical and Relational Learning -- Two Examples of Computational Creativity: ILP Multiple Predicate Synthesis and the ‘Assets’ in Theorem Proving -- Logical Aspects of the Measures of Interestingness of Association Rules -- Text and Web Mining -- Clustering the Web 2.0 -- Induction in Multi-Label Text Classification Domains -- Cluster-Lift Method for Mapping Research Activities over a Concept Tree -- On Concise Representations of Frequent Patterns Admitting Negation -- Classification and Beyond -- A System to Detect Inconsistencies between a Domain Expert’s Different Perspectives on (Classification) Tasks -- The Dynamics of Multiagent Q-Learning in Commodity Market Resource Allocation -- Simple Algorithms for Frequent Item Set Mining -- Monte Carlo Feature Selection and Interdependency Discovery in Supervised Classification -- Machine Learning Methods in Automatic Image Annotation -- Neural Networks and Other Nature Inspired Approaches -- Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework -- Machine Learning in Vector Models of Neural Networks -- Nature Inspired Multi-Swarm Heuristics for Multi-Knowledge Extraction -- Discovering Data Structures Using Meta-learning, Visualization and Constructive Neural Networks -- Neural Network and Artificial Immune Systems for Malware and Network Intrusion Detection -- Immunocomputing for Speaker Recognition.
520 _aThis is the second volume of a large two-volume editorial project we wish to dedicate to the memory of the late Professor Ryszard S. Michalski who passed away in 2007. He was one of the fathers of machine learning, an exciting and relevant, both from the practical and theoretical points of view, area in modern computer science and information technology. His research career started in the mid-1960s in Poland, in the Institute of Automation, Polish Academy of Sciences in Warsaw, Poland. He left for the USA in 1970, and since then had worked there at various universities, notably, at the University of Illinois at Urbana – Champaign and finally, until his untimely death, at George Mason University. We, the editors, had been lucky to be able to meet and collaborate with Ryszard for years, indeed some of us knew him when he was still in Poland. After he started working in the USA, he was a frequent visitor to Poland, taking part at many conferences until his death. We had also witnessed with a great personal pleasure honors and awards he had received over the years, notably when some years ago he was elected Foreign Member of the Polish Academy of Sciences among some top scientists and scholars from all over the world, including Nobel prize winners. Professor Michalski’s research results influenced very strongly the development of machine learning, data mining, and related areas. Also, he inspired many established and younger scholars and scientists all over the world. We feel very happy that so many top scientists from all over the world agreed to pay the last tribute to Professor Michalski by writing papers in their areas of research. These papers will constitute the most appropriate tribute to Professor Michalski, a devoted scholar and researcher. Moreover, we believe that they will inspire many newcomers and younger researchers in the area of broadly perceived machine learning, data analysis and data mining. The papers included in the two volumes, Machine Learning I and Machine Learning II, cover diverse topics, and various aspects of the fields involved. For convenience of the potential readers, we will now briefly summarize the contents of the particular chapters.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aRas, Zbigniew W.
_eeditor.
700 1 _aWierzchon, Slawomir T.
_eeditor.
700 1 _aKacprzyk, Janusz.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642051784
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v263
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-3-642-05179-1
596 _a19
942 _cLIBRO_ELEC
999 _c201623
_d201623