All Stories

  1. Resource-efficient fast prediction in healthcare data analytics: A pruned Random Forest regression approach
  2. A non-canonical hybrid metaheuristic approach to adaptive data stream classification
  3. DeTrac: Transfer Learning of Class Decomposed Medical Images in Convolutional Neural Networks
  4. DeepHist: Towards a Deep Learning-based Computational History of Trends in the NIPS
  5. EACD: evolutionary adaptation to concept drifts in data streams
  6. Leap2Trend: A Temporal Word Embedding Approach for Instant Detection of Emerging Scientific Trends
  7. RED-GENE: An Evolutionary Game Theoretic Approach to Adaptive Data Stream Classification
  8. TONE
  9. A Non-Intrusive Heuristic for Energy Messaging Intervention Modeled Using a Novel Agent-Based Approach
  10. Internet of Things and data mining: From applications to techniques and systems
  11. Data Stream Clustering for Real-Time Anomaly Detection: An Application to Insider Threats
  12. Activity Recognition with Evolving Data Streams
  13. Edge Machine Learning: Enabling Smart Internet of Things Applications
  14. Ensemble Dynamics in Non-stationary Data Stream Classification
  15. Adaptive One-Class Ensemble-based Anomaly Detection: An Application to Insider Threats
  16. Imitation Learning
  17. An Agent-Based Collective Model to Simulate Peer Pressure Effect on Energy Consumption
  18. Cascading Probability Distributions in Agent-Based Models: An Application to Behavioural Energy Wastage
  19. OntoPeFeGe: Ontology-Based Personalized Feedback Generator
  20. k-NN Embedding Stability for word2vec Hyper-Parametrisation in Scientific Text
  21. Deep imitation learning for 3D navigation tasks
  22. Evaluating the quality of the ontology-based auto-generated questions
  23. A Hybrid Agent-Based and Probabilistic Model for Fine-Grained Behavioural Energy Waste Simulation
  24. On expressiveness and uncertainty awareness in rule-based classification for data streams
  25. RedEdge: A Novel Architecture for Big Data Processing in Mobile Edge Computing Environments
  26. Deep reward shaping from demonstrations
  27. A genetic algorithm approach to optimising random forests applied to class engineered data
  28. Expressive modeling for trusted big data analytics: techniques and applications in sentiment analysis
  29. A Statistical Learning Method to Fast Generalised Rule Induction Directly from Raw Measurements
  30. A rule dynamics approach to event detection in Twitter with its application to sports and politics
  31. Clustering-Based Spatio-Temporal Analysis of Big Atmospheric Data
  32. A fine-grained Random Forests using class decomposition: an application to medical diagnosis
  33. Spatio-temporal analysis of Greenhouse Gas data via clustering techniques
  34. Adaptive mobile activity recognition system with evolving data streams
  35. An efficient Self-Organizing Active Contour model for image segmentation
  36. Autonomic Discovery of News Evolvement in Twitter
  37. A Scalable Expressive Ensemble Learning Using Random Prism: A MapReduce Approach
  38. Advances in Social Media Analysis
  39. Extraction of Unexpected Rules from Twitter Hashtags and its Application to Sport Events
  40. Predicting Hot-Spots in Distributed Cloud Databases Using Association Rule Mining
  41. Text stream mining for Massive Open Online Courses: review and perspectives
  42. Fault detection in non-linear systems based on GP-EKF and GP-UKF algorithms
  43. Random forests: from early developments to recent advancements
  44. Large Scale and Big Data
  45. Data stream mining in ubiquitous environments: state-of-the-art and current directions
  46. Bigger data for big data: From Twitter to brain–computer interfaces
  47. Mining Recurring Concepts in a Dynamic Feature Space
  48. A Concurrent SOM-Based Chan-Vese Model for Image Segmentation
  49. Adaptive data stream mining for wireless sensor networks
  50. A Survey of SOM-Based Active Contour Models for Image Segmentation
  51. Adopted Data Mining Methods
  52. Astronomical Data Mining
  53. Astronomy and Big Data
  54. Astronomy, Galaxies and Stars: An Overview
  55. Background
  56. Conclusion and FutureWork
  57. Conclusions, Discussion and Future Work
  58. Context-Aware PDM (Coll-Stream)
  59. Development of Data Mining Models
  60. Diversified Random Forests Using Random Subspaces
  61. Experimentation Results
  62. Implementation of Pocket Data Mining
  63. Introduction
  64. Introduction
  65. Pocket Data Mining Framework
  66. Pocket Data Mining
  67. Potential Applications of Pocket Data Mining
  68. Research Methodology
  69. COLLABORATIVE DATA STREAM MINING IN UBIQUITOUS ENVIRONMENTS USING DYNAMIC CLASSIFIER SELECTION
  70. An Information-Theoretic Approach for Setting the Optimal Number of Decision Trees in Random Forests
  71. An entropy-based approach to enhancing Random Forests
  72. MCCTA 2013: Welcome Message from the Workshop Organizers
  73. Open Mobile Miner: A Toolkit for Building Situation-Aware Data Mining Applications
  74. An overview of interactive visual data mining techniques for knowledge discovery
  75. Interactive self-adaptive clutter-aware visualisation for mobile data mining
  76. TRCM: A Methodology for Temporal Analysis of Evolving Concepts in Twitter
  77. Rule Type Identification Using TRCM for Trend Analysis in Twitter
  78. Data Science and Distributed Intelligence: Recent Developments and Future Insights
  79. Identifying Uncertain Galaxy Morphologies Using Unsupervised Learning
  80. Scaling up Data Mining Techniques to Large Datasets Using Parallel and Distributed Processing
  81. Deploying Mobile Software Agents for Distributed Data Mining on Wireless Sensor Networks: A Comparative Analysis
  82. StreamAR: Incremental and Active Learning with Evolving Sensory Data for Activity Recognition
  83. MARS: A Personalised Mobile Activity Recognition System
  84. Mobile Data Stream Mining: From Algorithms to Applications
  85. Journeys to Data Mining
  86. GARF: Towards Self-optimised Random Forests
  87. Density-Based Projected Clustering of Data Streams
  88. Advanced Machine Learning Technologies and Applications
  89. Mobile Activity Recognition Using Ubiquitous Data Stream Mining
  90. Introduction
  91. CBARS: Cluster Based Classification for Activity Recognition Systems
  92. Homogeneous and Heterogeneous Distributed Classification for Pocket Data Mining
  93. eRules: A Modular Adaptive Classification Rule Learning Algorithm for Data Streams
  94. Preface to the Third IEEE ICDM Workshop on Knowledge Discovery from Climate Data
  95. Advances in data stream mining
  96. Distributed hoeffding trees for pocket data mining
  97. RA-SAX: Resource-Aware Symbolic Aggregate Approximation for Mobile ECG Analysis
  98. KB-CB-N classification: Towards unsupervised approach for supervised learning
  99. Knowledge discovery from sensor data (SensorKDD)
  100. Energy conservation in wireless sensor networks: a rule-based approach
  101. Energy-Aware Data Processing Techniques for Wireless Sensor Networks: A Review
  102. Context-Aware Collaborative Data Stream Mining in Ubiquitous Devices
  103. Distributed Classification for Pocket Data Mining
  104. Advances in data stream mining for mobile and ubiquitous environments
  105. Resource-aware ECG analysis on mobile devices
  106. Enabling Scalable Semantic Reasoning for Mobile Services
  107. Clutter-Adaptive Visualization for Mobile Data Mining
  108. Pocket Data Mining: Towards Collaborative Data Mining in Mobile Computing Environments
  109. Adaptive Clutter-Aware Visualization for Mobile Data Stream Mining
  110. Corona: Energy-Efficient Multi-query Processing in Wireless Sensor Networks
  111. Distributed data stream classification for wireless sensor networks
  112. Scientific Data Mining and Knowledge Discovery
  113. Situation-Aware Adaptive Visualization for Sensory Data Stream Mining
  114. Enabling Scalable Semantic Reasoning for Mobile Services
  115. An analytical study of central and in-network data processing for wireless sensor networks
  116. Cost efficient, adaptive reasoning strategies for pervasive service discovery
  117. Knowledge discovery from data streams
  118. Introduction
  119. A Weighted Approach to Partial Matching for Mobile Reasoning
  120. Data Stream Mining
  121. Data Stream Mining Using Granularity-Based Approach
  122. Mobile Data Mining for Intelligent Healthcare Support
  123. Knowledge Discovery from Sensor Data
  124. Clustering Distributed Time Series in Sensor Networks
  125. Foundations of Adaptive Data Stream Mining for Mobile and Embedded Applications
  126. A Rule Learning Approach to Energy Efficient Clustering in Wireless Sensor Networks
  127. ARTS: Adaptive Rule Triggers on Sensors for Energy Conservation in Applications using Coarse-Granularity Data
  128. Using association rules for energy conservation in wireless sensor networks
  129. On the Integration of Data Stream Clustering into a Query Processor for Wireless Sensor Networks
  130. Learning from Data Streams
  131. Resource-aware Online Data Mining in Wireless Sensor Networks
  132. DETECTION AND CLASSIFICATION OF CHANGES IN EVOLVING DATA STREAMS
  133. A Holistic Approach for Resource-aware Adaptive Data Stream Mining
  134. Mining data streams
  135. Data Stream Processing in Sensor Networks
  136. Introduction
  137. A Survey of Classification Methods in Data Streams
  138. Data Science and Distributed Intelligence