Petra Perner




Machine Learning and Data Mining in Pattern Recognition


Proceedings of the 9th International Conference on Machine Learning and Data Mining in Pattern Recognition


Springer Berlin Heidelberg

BOOK (manifestation)

  • Book: 978-3-642-39712-7 (eBook)
  • Book: 978-3-642-39711-0 (Book)

  • Related objects


  • Conference: International Workshop On Machine Learning And Data Mining In Pattern Recognition


  • BookChapter: Mining Groups of Common Interest: Discovering Topical Communities with Network Flows
  • BookChapter: Shifting Concepts to Their Associative Concepts via Bridges
  • BookChapter: Classification and Outlier Detection Based on Topic Based Pattern Synthesis
  • BookChapter: Unsupervised Tagging of Spanish Lyrics Dataset Using Clustering
  • BookChapter: Discovering Frequent Itemsets on Uncertain Data: A Systematic Review
  • BookChapter: TISA: Topic Independence Scoring Algorithm
  • BookChapter: Analytic Feature Selection for Support Vector Machines
  • BookChapter: Improving the Efficiency of Distributed Data Mining Using an Adjustment Work Flow
  • BookChapter: Preceding Rule Induction with Instance Reduction Methods
  • BookChapter: Using Turning Point Detection to Obtain Better Regression Trees
  • BookChapter: A Comparative Study on Mobile Visual Recognition
  • BookChapter: Applying a Lightweight Iterative Merging Chinese Segmentation in Web Image Annotation
  • BookChapter: Large Scale Visual Classification with Many Classes
  • BookChapter: Information Gap Analysis for Decision Support Systems in Evidence-Based Medicine
  • BookChapter: EEG Feature Selection Based on Time Series Classification
  • BookChapter: Partial Discharge Analysis and Inspection Alert Generation in High Power Transformers: A Case Study of an Autotransformer Bank at Eletrobrás-ELETRONORTE Vila do Conde Station
  • BookChapter: Multi Model Transfer Learning with RULES Family
  • BookChapter: Automatic Classification of Web Databases Using Domain-Dictionaries
  • BookChapter: Estimating and Forecasting Network Traffic Performance Based on Statistical Patterns Observed in SNMP Data
  • BookChapter: Pacc - A Discriminative and Accuracy Correlated Measure for Assessment of Classification Results
  • BookChapter: The Gapped Spectrum Kernel for Support Vector Machines
  • BookChapter: Using Part of Speech N-Grams for Improving Automatic Speech Recognition of Polish
  • BookChapter: Smart Meter Data Analysis for Power Theft Detection
  • BookChapter: Decremental Learning of Evolving Fuzzy Inference Systems: Application to Handwritten Gesture Recognition
  • BookChapter: Dynamic-Radius Species-Conserving Genetic Algorithm for the Financial Forecasting of Dow Jones Index Stocks
  • BookChapter: Pre-release Box-Office Success Prediction for Motion Pictures
  • BookChapter: A Lightweight Combinatorial Approach for Inferring the Ground Truth from Multiple Annotators
  • BookChapter: An Efficient and Scalable Algorithm for Mining Maximal
  • BookChapter: Satellite Image Mining for Census Collection: A Comparative Study with Respect to the Ethiopian Hinterland
  • BookChapter: SOM++: Integration of Self-Organizing Map and K-Means++ Algorithms
  • BookChapter: Optimal Time Segments for Stress Detection
  • BookChapter: A Pattern Based Two-Stage Text Classifier
  • BookChapter: Density Ratio Estimation in Support Vector Machine for Better Generalization: Study on Direct Marketing Prediction
  • BookChapter: Relation Decomposition: The Theory
  • BookChapter: Feature Learning for Detection and Prediction of Freezing of Gait in Parkinson’s Disease
  • BookChapter: An Empirical Study of Reducing Multiclass Classification Methodologies
  • BookChapter: Multi-document Text Summarization Using Topic Model and Fuzzy Logic
  • BookChapter: Typhoon Damage Scale Forecasting with Self-Organizing Maps Trained by Selective Presentation Learning
  • BookChapter: When Classification becomes a Problem: Using Branch-and-Bound to Improve Classification Efficiency
  • BookChapter: Evaluation of Hyperspectral Image Classification Using Random Forest and Fukunaga-Koontz Transform
  • BookChapter: Personalized Expert-Based Recommender System: Training C-SVM for Personalized Expert Identification
  • BookChapter: Lazy Overfitting Control
  • BookChapter: Area under the Distance Threshold Curve as an Evaluation Measure for Probabilistic Classifiers
  • BookChapter: 3D Geovisualisation Techniques Applied in Spatial Data Mining
  • BookChapter: A Single-Domain, Representation-Learning Model for Big Data Classification of Network Intrusion
  • BookChapter: Accuracy-Based Classification EM: Combining Clustering with Prediction
  • BookChapter: DCA Based Algorithms for Feature Selection in Semi-supervised Support Vector Machines
  • BookChapter: Relevance as a Metric for Evaluating Machine Learning Algorithms
  • BookChapter: Sign Language Recognition with Support Vector Machines and Hidden Conditional Random Fields: Going from Fingerspelling to Natural Articulated Words


  • Computer Science
  • Algorithm Analysis And Problem Complexity
  • Data Mining And Knowledge Discovery
  • Artificial Intelligence (Incl. Robotics)
  • Pattern Recognition

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    22 TRIPLES      18 PREDICATES      23 URIs      13 LITERALS

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    2 sg:chapterCount 49
    3 sg:copyrightHolder Springer-Verlag Berlin Heidelberg
    4 sg:copyrightYear 2013
    5 sg:ddsId 248869
    6 sg:description Proceedings of the 9th International Conference on Machine Learning and Data Mining in Pattern Recognition
    7 sg:editionNumber 1
    8 sg:hasConference conferences:1ae3bcc9dfb6b7ef3e80007c2c68b6a4
    9 sg:hasContribution contributions:cbb238e8f6d539e8918da2802b917a88
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    15 sg:language En
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    17 sg:publisher Springer Berlin Heidelberg
    18 sg:scigraphId 02435fb39abd14c425793da0968adfd2
    19 sg:subtitle 9th International Conference, MLDM 2013, New York, NY, USA, July 19-25, 2013, Proceedings
    20 sg:title Machine Learning and Data Mining in Pattern Recognition
    21 rdf:type sg:BookEdition
    22 rdfs:label BookEdition: Machine Learning and Data Mining in Pattern Recognition

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