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  • 1
    UID:
    b3kat_BV043209428
    Format: 1 Online Ressource (XXI, 364 Seiten) , Illustrationen, Diagramme
    ISBN: 9783319118123
    Series Statement: Lecture Notes in Computer Science 8777
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-319-11811-6
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Wissensextraktion ; Data Mining ; Maschinelles Lernen ; Algorithmische Lerntheorie ; Konferenzschrift
    URL: Volltext  (URL des Erstveröffentlichers)
    Author information: Džeroski, Sašo 1968-
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    almahu_BV042079860
    Format: XXI, 364 S. : , Ill., graph. Darst. ; , 235 mm x 155 mm.
    ISBN: 3-319-11811-0 , 978-3-319-11812-3
    Series Statement: Lecture Notes in Computer Science 8777 : Lecture notes in artificial intelligence
    Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-3-319-11812-3
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Wissensextraktion ; Data Mining ; Maschinelles Lernen ; Algorithmische Lerntheorie ; Konferenzschrift ; Konferenzschrift
    Author information: Džeroski, Sašo, 1968-
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    UID:
    gbv_1659292549
    Format: Online-Ressource (XXII, 364 p. 111 illus, online resource)
    ISBN: 9783319118123
    Series Statement: Lecture Notes in Computer Science 8777
    Content: This book constitutes the proceedings of the 17th International Conference on Discovery Science, DS 2014, held in Bled, Slovenia, in October 2014. The 30 full papers included in this volume were carefully reviewed and selected from 62 submissions. The papers cover topics such as: computational scientific discovery; data mining and knowledge discovery; machine learning and statistical methods; computational creativity; mining scientific data; data and knowledge visualization; knowledge discovery from scientific literature; mining text, unstructured and multimedia data; mining structured and relational data; mining temporal and spatial data; mining data streams; network analysis; discovery informatics; discovery and experimental workflows; knowledge capture and scientific ontologies; data and knowledge integration; logic and philosophy of scientific discovery; and applications of computational methods in various scientific domains
    Note: Literaturangaben , Explaining Mixture Models through Semantic Pattern Mining and Banded Matrix VisualizationBig Data Analysis of StockTwits to Predict Sentiments in the Stock Market -- Synthetic Sequence Generator for Recommender Systems - Memory Biased Random Walk on a Sequence Multilayer Network -- Predicting Sepsis Severity from Limited Temporal Observations -- Completion Time and Next Activity Prediction of Processes Using Sequential Pattern Mining -- Antipattern Discovery in Ethiopian Bagana Songs -- Categorize, Cluster, and Classify: A 3-C Strategy for Scientific Discovery in the Medical Informatics Platform of the Human Brain Project -- Multilayer Clustering: A Discovery Experiment on Country Level Trading Data -- Medical Document Mining Combining Image Exploration and Text Characterization -- Mining Cohesive Itemsets in Graphs -- Mining Rank Data -- Link Prediction on the Semantic MEDLINE Network: An Approach to Literature-Based Discovery -- Medical Image Retrieval Using Multimodal Data -- Fast Computation of the Tree Edit Distance between Unordered Trees Using IP Solvers -- Probabilistic Active Learning: Towards Combining Versatility, Optimality and Efficiency -- Incremental Learning with Social Media Data to Predict Near Real-Time Events -- Stacking Label Features for Learning Multilabel Rules -- Selective Forgetting for Incremental Matrix Factorization in Recommender Systems -- Providing Concise Database Covers Instantly by Recursive Tile Sampling -- Resampling-Based Framework for Estimating Node Centrality of Large Social Network -- Detecting Maximum k-Plex with Iterative Proper l-Plex Search -- Exploiting Bhattacharyya Similarity Measure to Diminish User Cold-Start Problem in Sparse Data -- Failure Prediction - An Application in the Railway Industry -- Wind Power Forecasting Using Time Series Cluster Analysis -- Feature Selection in Hierarchical Feature Spaces -- Incorporating Regime Metrics into Latent Variable Dynamic Models to Detect Early-Warning Signals of Functional Changes in Fisheries Ecology -- An Efficient Algorithm for Enumerating Chordless Cycles and Chordless Paths -- Algorithm Selection on Data Streams -- Sparse Coding for Key Node Selection over Networks -- Variational Dependent Multi-output Gaussian Process Dynamical Systems.
    Additional Edition: ISBN 9783319118116
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-331-91181-1-6
    Additional Edition: Erscheint auch als Druck-Ausgabe Discovery science Cham [u.a.] : Springer, 2014 ISBN 3319118110
    Additional Edition: ISBN 9783319118123
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Wissensextraktion ; Data Mining ; Maschinelles Lernen ; Algorithmische Lerntheorie ; Konferenzschrift
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
    URL: Cover
    Author information: Džeroski, Sašo 1968-
    Library Location Call Number Volume/Issue/Year Availability
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  • 4
    UID:
    almahu_9947363721502882
    Format: XXII, 364 p. 111 illus. , online resource.
    ISBN: 9783319118123
    Series Statement: Lecture Notes in Computer Science, 8777
    Content: This book constitutes the proceedings of the 17th International Conference on Discovery Science, DS 2014, held in Bled, Slovenia, in October 2014. The 30 full papers included in this volume were carefully reviewed and selected from 62 submissions. The papers cover topics such as: computational scientific discovery; data mining and knowledge discovery; machine learning and statistical methods; computational creativity; mining scientific data; data and knowledge visualization; knowledge discovery from scientific literature; mining text, unstructured and multimedia data; mining structured and relational data; mining temporal and spatial data; mining data streams; network analysis; discovery informatics; discovery and experimental workflows; knowledge capture and scientific ontologies; data and knowledge integration; logic and philosophy of scientific discovery; and applications of computational methods in various scientific domains.
    Note: Explaining Mixture Models through Semantic Pattern Mining and Banded Matrix Visualization -- Big Data Analysis of StockTwits to Predict Sentiments in the Stock Market -- Synthetic Sequence Generator for Recommender Systems – Memory Biased Random Walk on a Sequence Multilayer Network -- Predicting Sepsis Severity from Limited Temporal Observations -- Completion Time and Next Activity Prediction of Processes Using Sequential Pattern Mining -- Antipattern Discovery in Ethiopian Bagana Songs -- Categorize, Cluster, and Classify: A 3-C Strategy for Scientific Discovery in the Medical Informatics Platform of the Human Brain Project -- Multilayer Clustering: A Discovery Experiment on Country Level Trading Data -- Medical Document Mining Combining Image Exploration and Text Characterization -- Mining Cohesive Itemsets in Graphs -- Mining Rank Data -- Link Prediction on the Semantic MEDLINE Network: An Approach to Literature-Based Discovery -- Medical Image Retrieval Using Multimodal Data -- Fast Computation of the Tree Edit Distance between Unordered Trees Using IP Solvers -- Probabilistic Active Learning: Towards Combining Versatility, Optimality and Efficiency -- Incremental Learning with Social Media Data to Predict Near Real-Time Events -- Stacking Label Features for Learning Multilabel Rules -- Selective Forgetting for Incremental Matrix Factorization in Recommender Systems -- Providing Concise Database Covers Instantly by Recursive Tile Sampling -- Resampling-Based Framework for Estimating Node Centrality of Large Social Network -- Detecting Maximum k-Plex with Iterative Proper l-Plex Search -- Exploiting Bhattacharyya Similarity Measure to Diminish User Cold-Start Problem in Sparse Data -- Failure Prediction – An Application in the Railway Industry -- Wind Power Forecasting Using Time Series Cluster Analysis -- Feature Selection in Hierarchical Feature Spaces -- Incorporating Regime Metrics into Latent Variable Dynamic Models to Detect Early-Warning Signals of Functional Changes in Fisheries Ecology -- An Efficient Algorithm for Enumerating Chordless Cycles and Chordless Paths -- Algorithm Selection on Data Streams -- Sparse Coding for Key Node Selection over Networks -- Variational Dependent Multi-output Gaussian Process Dynamical Systems.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783319118116
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 5
    UID:
    gbv_810688271
    ISBN: 9783319118123
    Series Statement: Lecture Notes in Computer Science 8777
    In: Džeroski, Sašo, 1968 -, Discovery Science, Cham [u.a.] : Springer, 2014, (2014), Seite 204-215, 9783319118123
    In: year:2014
    In: pages:204-215
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 6
    UID:
    gbv_799385441
    ISBN: 9783319118123
    Series Statement: Lecture Notes in Computer Science 8777
    In: Džeroski, Sašo, 1968 -, Discovery Science, Cham [u.a.] : Springer, 2014, (2014), Seite 168-179, 9783319118123
    In: year:2014
    In: pages:168-179
    Language: English
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