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  • 1
    UID:
    edoccha_BV049320876
    Format: 1 Online-Ressource (XII, 179 p. 48 illus., 43 illus. in color).
    Edition: 1st ed. 2023
    ISBN: 978-3-031-39144-6
    Series Statement: Communications in Computer and Information Science 1805
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-39143-9
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-39145-3
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 2
    UID:
    edocfu_BV049320876
    Format: 1 Online-Ressource (XII, 179 p. 48 illus., 43 illus. in color).
    Edition: 1st ed. 2023
    ISBN: 978-3-031-39144-6
    Series Statement: Communications in Computer and Information Science 1805
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-39143-9
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-39145-3
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 3
    UID:
    almahu_BV019767684
    Format: VI, 189 S. : , graph. Darst.
    ISBN: 3-540-25082-4
    Series Statement: Lecture Notes in Computer Science 3377
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Wissensextraktion ; Datenbanksystem ; Induktion ; Data Mining ; Induktion ; Konferenzschrift ; Kongress ; Konferenzschrift ; Konferenzschrift ; Konferenzschrift ; Konferenzschrift
    URL: Cover
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  • 4
    UID:
    b3kat_BV049320876
    Format: 1 Online-Ressource (XII, 179 p. 48 illus., 43 illus. in color)
    Edition: 1st ed. 2023
    ISBN: 9783031391446
    Series Statement: Communications in Computer and Information Science 1805
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-39143-9
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-39145-3
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 5
    UID:
    b3kat_BV022354914
    Format: 1 Online-Ressource (VI, 189 S.) , graph. Darst.
    ISBN: 3540250824 , 9783540250821
    Series Statement: Lecture Notes in Computer Science 3377
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Wissensextraktion ; Datenbanksystem ; Induktion ; Data Mining ; Induktion ; Konferenzschrift
    URL: Volltext  (lizenzpflichtig)
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  • 6
    UID:
    almafu_BV049320876
    Format: 1 Online-Ressource (XII, 179 p. 48 illus., 43 illus. in color).
    Edition: 1st ed. 2023
    ISBN: 978-3-031-39144-6
    Series Statement: Communications in Computer and Information Science 1805
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-39143-9
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-031-39145-3
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 7
    UID:
    b3kat_BV047262600
    Format: 1 Online-Ressource (953 Seiten) , Illustrationen
    ISBN: 9781611972801
    Content: Welcome to SDM 2010 --
    Content: The Tenth SIAM International Conference on Data Mining. SDM 2010 continues a series of conferences focusing on the theory and practice of data mining as applied to data sets in science, engineering, biomedicine, and the social sciences, among others. Following the tradition of past conferences, the main technical program is accompanied by a number of specialized workshops, minisymposia, tutorials, a plenary panel, and the doctoral forum. The keynote talks form the centerpiece of SDM 2010: Stephen Muggleton from the Imperial College, London, UK; Grace Wahba from the University of Wisconsin; Phillip Gibbons from Intel Research; and Vipin Kumar from the University of Minnesota will share their experience and vision with us.
    Content: The conference also has a diverse and rich program; apart from our strong technical program of contributed papers, there is a rich set of integrated tutorials on a wide range of topics: outlier detection, mining sparse representations, ranking methods in machine learning, and supervised and unsupervised ensemble methods. The main program is also further complemented by a group of focused workshops and a minisymposium on current and emerging topics such as data mining for sustainable development, high-performance analytics, text mining, data mining for a smarter infrastructure, an invited workshop on clustering theory and applications, and a minisymposium on natural language-based data mining. Building on the success of last year's doctoral forum, SDM 2010 will see a continuation of this popular event, which will be held along with the plenary panel on the second day of the conference.
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-0-89871-703-7
    Language: English
    Keywords: Konferenzschrift
    URL: Volltext  (URL des Erstveröffentlichers)
    Author information: Liu, Bing 1963-
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  • 8
    UID:
    almahu_9947363955502882
    Format: VIII, 200 p. , online resource.
    ISBN: 9783540318415
    Series Statement: Lecture Notes in Computer Science, 3377
    Note: Invited Paper -- Models and Indices for Integrating Unstructured Data with a Relational Database -- Contributed Papers -- Constraint Relaxations for Discovering Unknown Sequential Patterns -- Mining Formal Concepts with a Bounded Number of Exceptions from Transactional Data -- Theoretical Bounds on the Size of Condensed Representations -- Mining Interesting XML-Enabled Association Rules with Templates -- Database Transposition for Constrained (Closed) Pattern Mining -- An Efficient Algorithm for Mining String Databases Under Constraints -- An Automata Approach to Pattern Collections -- Implicit Enumeration of Patterns -- Condensed Representation of EPs and Patterns Quantified by Frequency-Based Measures.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783540250821
    Language: English
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  • 9
    UID:
    almahu_9947364305702882
    Format: XXIII, 698 p. , online resource.
    ISBN: 9783540874812
    Series Statement: Lecture Notes in Computer Science, 5212
    Content: This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
    Note: Regular Papers -- Exceptional Model Mining -- A Joint Topic and Perspective Model for Ideological Discourse -- Effective Pruning Techniques for Mining Quasi-Cliques -- Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain -- Fitted Natural Actor-Critic: A New Algorithm for Continuous State-Action MDPs -- A New Natural Policy Gradient by Stationary Distribution Metric -- Towards Machine Learning of Grammars and Compilers of Programming Languages -- Improving Classification with Pairwise Constraints: A Margin-Based Approach -- Metric Learning: A Support Vector Approach -- Support Vector Machines, Data Reduction, and Approximate Kernel Matrices -- Mixed Bregman Clustering with Approximation Guarantees -- Hierarchical, Parameter-Free Community Discovery -- A Genetic Algorithm for Text Classification Rule Induction -- Nonstationary Gaussian Process Regression Using Point Estimates of Local Smoothness -- Kernel-Based Inductive Transfer -- State-Dependent Exploration for Policy Gradient Methods -- Client-Friendly Classification over Random Hyperplane Hashes -- Large-Scale Clustering through Functional Embedding -- Clustering Distributed Sensor Data Streams -- A Novel Scalable and Data Efficient Feature Subset Selection Algorithm -- Robust Feature Selection Using Ensemble Feature Selection Techniques -- Effective Visualization of Information Diffusion Process over Complex Networks -- Actively Transfer Domain Knowledge -- A Unified View of Matrix Factorization Models -- Parallel Spectral Clustering -- Classification of Multi-labeled Data: A Generative Approach -- Pool-Based Agnostic Experiment Design in Linear Regression -- Distribution-Free Learning of Bayesian Network Structure -- Assessing Nonlinear Granger Causality from Multivariate Time Series -- Clustering Via Local Regression -- Decomposable Families of Itemsets -- Transferring Instances for Model-Based Reinforcement Learning -- A Simple Model for Sequences of Relational State Descriptions -- Semi-Supervised Boosting for Multi-Class Classification -- A Joint Segmenting and Labeling Approach for Chinese Lexical Analysis -- Transferred Dimensionality Reduction -- Multiple Manifolds Learning Framework Based on Hierarchical Mixture Density Model -- Estimating Sales Opportunity Using Similarity-Based Methods -- Learning MDP Action Models Via Discrete Mixture Trees -- Continuous Time Bayesian Networks for Host Level Network Intrusion Detection -- Data Streaming with Affinity Propagation -- Semi-supervised Discriminant Analysis Via CCCP -- Demo Papers -- A Visualization-Based Exploratory Technique for Classifier Comparison with Respect to Multiple Metrics and Multiple Domains -- Pleiades: Subspace Clustering and Evaluation -- SEDiL: Software for Edit Distance Learning -- Monitoring Patterns through an Integrated Management and Mining Tool -- A Knowledge-Based Digital Dashboard for Higher Learning Institutions -- SINDBAD and SiQL: An Inductive Database and Query Language in the Relational Model.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783540874805
    Language: English
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  • 10
    UID:
    gbv_1647401186
    Format: Online-Ressource (digital)
    ISBN: 9783540874799
    Series Statement: Lecture Notes in Computer Science 5211
    Content: Invited Talks (Abstracts) -- Industrializing Data Mining, Challenges and Perspectives -- From Microscopy Images to Models of Cellular Processes -- Data Clustering: 50 Years Beyond K-means -- Learning Language from Its Perceptual Context -- The Role of Hierarchies in Exploratory Data Mining -- Machine Learning Journal Abstracts -- Rollout Sampling Approximate Policy Iteration -- New Closed-Form Bounds on the Partition Function -- Large Margin vs. Large Volume in Transductive Learning -- Incremental Exemplar Learning Schemes for Classification on Embedded Devices -- A Collaborative Filtering Framework Based on Both Local User Similarity and Global User Similarity -- A Critical Analysis of Variants of the AUC -- Improving Maximum Margin Matrix Factorization -- Data Mining and Knowledge Discovery Journal Abstracts -- Finding Reliable Subgraphs from Large Probabilistic Graphs -- A Space Efficient Solution to the Frequent String Mining Problem for Many Databases -- The Boolean Column and Column-Row Matrix Decompositions -- SkyGraph: An Algorithm for Important Subgraph Discovery in Relational Graphs -- Mining Conjunctive Sequential Patterns -- Adequate Condensed Representations of Patterns -- Two Heads Better Than One: Pattern Discovery in Time-Evolving Multi-aspect Data -- Regular Papers -- TOPTMH: Topology Predictor for Transmembrane ?-Helices -- Learning to Predict One or More Ranks in Ordinal Regression Tasks -- Cascade RSVM in Peer-to-Peer Networks -- An Algorithm for Transfer Learning in a Heterogeneous Environment -- Minimum-Size Bases of Association Rules -- Combining Classifiers through Triplet-Based Belief Functions -- An Improved Multi-task Learning Approach with Applications in Medical Diagnosis -- Semi-supervised Laplacian Regularization of Kernel Canonical Correlation Analysis -- Sequence Labelling SVMs Trained in One Pass -- Semi-supervised Classification from Discriminative Random Walks -- Learning Bidirectional Similarity for Collaborative Filtering -- Bootstrapping Information Extraction from Semi-structured Web Pages -- Online Multiagent Learning against Memory Bounded Adversaries -- Scalable Feature Selection for Multi-class Problems -- Learning Decision Trees for Unbalanced Data -- Credal Model Averaging: An Extension of Bayesian Model Averaging to Imprecise Probabilities -- A Fast Method for Training Linear SVM in the Primal -- On the Equivalence of the SMO and MDM Algorithms for SVM Training -- Nearest Neighbour Classification with Monotonicity Constraints -- Modeling Transfer Relationships Between Learning Tasks for Improved Inductive Transfer -- Mining Edge-Weighted Call Graphs to Localise Software Bugs -- Hierarchical Distance-Based Conceptual Clustering -- Mining Frequent Connected Subgraphs Reducing the Number of Candidates -- Unsupervised Riemannian Clustering of Probability Density Functions -- Online Manifold Regularization: A New Learning Setting and Empirical Study -- A Fast Algorithm to Find Overlapping Communities in Networks -- A Case Study in Sequential Pattern Mining for IT-Operational Risk -- Tight Optimistic Estimates for Fast Subgroup Discovery -- Watch, Listen & Learn: Co-training on Captioned Images and Videos -- Parameter Learning in Probabilistic Databases: A Least Squares Approach -- Improving k-Nearest Neighbour Classification with Distance Functions Based on Receiver Operating Characteristics -- One-Class Classification by Combining Density and Class Probability Estimation -- Efficient Frequent Connected Subgraph Mining in Graphs of Bounded Treewidth -- Proper Model Selection with Significance Test -- A Projection-Based Framework for Classifier Performance Evaluation -- Distortion-Free Nonlinear Dimensionality Reduction -- Learning with L q? vs L 1-Norm Regularisation with Exponentially Many Irrelevant Features -- Catenary Support Vector Machines -- Exact and Approximate Inference for Annotating Graphs with Structural SVMs -- Extracting Semantic Networks from Text Via Relational Clustering -- Ranking the Uniformity of Interval Pairs -- Multiagent Reinforcement Learning for Urban Traffic Control Using Coordination Graphs -- StreamKrimp: Detecting Change in Data Streams.
    Content: This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
    Additional Edition: ISBN 9783540874782
    Additional Edition: Buchausg. u.d.T. Machine learning and knowledge discovery in databases ; 1 Berlin : Springer, 2008 ISBN 354087478X
    Additional Edition: ISBN 9783540874782
    Language: English
    Subjects: Computer Science
    RVK:
    URL: Volltext  (lizenzpflichtig)
    URL: Cover
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