All Stories

  1. Preference rules for label ranking: Mining patterns in multi-target relations
  2. Metalearning and Recommender Systems: A literature review and empirical study on the algorithm selection problem for Collaborative Filtering
  3. Using Metalearning for Parameter Tuning in Neural Networks
  4. A guidance of data stream characterization for meta-learning
  5. RELink
  6. TexRep: A Text Mining Framework for Online Reputation Monitoring
  7. Arbitrated Ensemble for Solar Radiation Forecasting
  8. Arbitrated Ensemble for Time Series Forecasting
  9. Learning Word Embeddings from the Portuguese Twitter Stream: A Study of Some Practical Aspects
  10. Metalearning
  11. Metalearning for Context-aware Filtering
  12. Scalable Online Top-N Recommender Systems
  13. Comparing comparables: an approach to accurate cross-country comparisons of health systems for effective healthcare planning and policy guidance
  14. Meta-learning to select the best meta-heuristic for the Traveling Salesman Problem: A comparison of meta-features
  15. Label Ranking Forests
  16. Active learning and data manipulation techniques for generating training examples in meta-learning
  17. Entropy-based discretization methods for ranking data
  18. AToMRS: A Tool to Monitor Recommender Systems
  19. CHADE: Metalearning with Classifier Chains for Dynamic Combination of Classifiers
  20. Can Metalearning Be Applied to Transfer on Heterogeneous Datasets?
  21. Collaborative Data Analysis in Hyperconnected Transportation Systems
  22. Combining Boosted Trees with Metafeature Engineering for Predictive Maintenance
  23. Exceptional Preferences Mining
  24. Learning from the News: Predicting Entity Popularity on Twitter
  25. RetweetPatterns: Detection of Spatio-Temporal Patterns of Retweets
  26. Selecting Collaborative Filtering Algorithms Using Metalearning
  27. Sentiment Aggregate Functions for Political Opinion Polling using Microblog Streams
  28. TimeMachine: Entity-Centric Search and Visualization of News Archives
  29. Towards Automatic Generation of Metafeatures
  30. TweeProfiles3: Visualization of Spatio-Temporal Patterns on Twitter
  31. Advances in Intelligent Data Analysis XV
  32. Customer segmentation in a large database of an online customized fashion business
  33. Combining regression models and metaheuristics to optimize space allocation in the retail industry
  34. POPmine: Tracking Political Opinion on the Web
  35. TwitterJam: Identification of mobility patterns in urban centers based on tweets
  36. Metalearning to choose the level of analysis in nested data: A case study on error detection in foreign trade statistics
  37. The weighted rank correlation coefficient
  38. Improving the accuracy of long-term travel time prediction using heterogeneous ensembles
  39. Distance-Based Decision Tree Algorithms for Label Ranking
  40. Estimating Fuel Consumption from GPS Data
  41. Pruning Bagging Ensembles with Metalearning
  42. Using Metalearning for Prediction of Taxi Trip Duration Using Different Granularity Levels
  43. Machine Learning and Knowledge Discovery in Databases
  44. Machine Learning and Knowledge Discovery in Databases
  45. A hybrid meta-learning architecture for multi-objective optimization of SVM parameters
  46. Distributed Environment Framework for Optimization Experiments
  47. MetaStream: A meta-learning based method for periodic algorithm selection in time-changing data
  48. An Empirical Methodology to Analyze the Behavior of Bagging
  49. A data warehouse to support web site automation
  50. Merging Decision Trees: A Case Study in Predicting Student Performance
  51. Monitoring Recommender Systems: A Business Intelligence Approach
  52. TweeProfiles: Detection of Spatio-temporal Patterns on Twitter
  53. Active selection of training instances for a random forest meta-learner
  54. Dimensions as Virtual Items: Improving the predictive ability of top-N recommender systems
  55. CN2-SD for Subgroup Discovery in a Highly Customized Textile Industry: A Case Study
  56. Multi-interval Discretization of Continuous Attributes for Label Ranking
  57. Space Allocation in the Retail Industry: A Decision Support System Integrating Evolutionary Algorithms and Regression Models
  58. Using statistics, visualization and data mining for monitoring the quality of meta-data in web portals
  59. Ensemble approaches for regression
  60. Combining a multi-objective optimization approach with meta-learning for SVM parameter selection
  61. Combining Meta-Learning with Multi-objective Particle Swarm Algorithms for SVM Parameter Selection: An Experimental Analysis
  62. Meta-Learning for Periodic Algorithm Selection in Time-Changing Data
  63. Multi-objective optimization and Meta-learning for SVM parameter selection
  64. A Meta-Learning Approach to Select Meta-Heuristics for the Traveling Salesman Problem Using MLP-Based Label Ranking
  65. An Experimental Study of the Combination of Meta-Learning with Particle Swarm Algorithms for SVM Parameter Selection
  66. Combining meta-learning and search techniques to select parameters for support vector machines
  67. Finding Interesting Contexts for Explaining Deviations in Bus Trip Duration Using Distribution Rules
  68. Integrating Data Mining and Optimization Techniques on Surgery Scheduling
  69. Multilayer Perceptron for Label Ranking
  70. Using Meta-learning to Recommend Meta-heuristics for the Traveling Salesman Problem
  71. Exploiting Additional Dimensions as Virtual Items on Top-N Recommender Systems
  72. Uncertainty sampling methods for selecting datasets in active meta-learning
  73. Selection of algorithms to solve traveling salesman problems using meta-learning1
  74. Combining Meta-learning and Active Selection of Datasetoids for Algorithm Selection
  75. Customer-Oriented and Eco-friendly Networks for Health Fashionable Goods – The CoReNet Approach
  76. Mining Association Rules for Label Ranking
  77. Uncertainty Sampling-Based Active Selection of Datasetoids for Meta-learning
  78. Inductive Transfer
  79. Metalearning
  80. Combining Meta-learning and Search Techniques to SVM Parameter Selection
  81. Using Meta-learning to Classify Traveling Salesman Problems
  82. A comprehensive comparison of ML algorithms for gene expression data classification
  83. A Similarity-Based Adaptation of Naive Bayes for Label Ranking: Application to the Metalearning Problem of Algorithm Recommendation
  84. Empirical Evaluation of Ranking Prediction Methods for Gene Expression Data Classification
  85. Intelligent Document Routing as a First Step towards Workflow Automation: A Case Study Implemented in SQL
  86. Meta‐learning approach to gene expression data classification
  87. The Effect of Varying Parameters and Focusing on Bus Travel Time Prediction
  88. Bioinspired Parameter Tuning of MLP Networks for Gene Expression Analysis: Quality of Fitness Estimates vs. Number of Solutions Analysed
  89. Detecting Errors in Foreign Trade Transactions: Dealing with Insufficient Data
  90. Ensemble Learning: A Study on Different Variants of the Dynamic Selection Approach
  91. Selection of Heuristics for the Job-Shop Scheduling Problem Based on the Prediction of Gaps in Machines
  92. UCI++: Improved Support for Algorithm Selection Using Datasetoids
  93. Metalearning
  94. The Impact of Contextual Information on the Accuracy of Existing Recommender Systems for Web Personalization
  95. Bio-Inspired Parameter Tunning of MLP Networks for Gene Expression Analysis
  96. Metalearning for Gene Expression Data Classification
  97. Rejoinder to letter to the editor from C. Genest and J-F. Plante concerning ?Pinto da Costa, J. & Soares, C. (2005) A weighted rank measure of correlation.?
  98. A Web-Based System to Monitor the Quality of Meta-Data in Web Portals
  99. Factor Analysis to Support the Visualization and Interpretation of Clusters of Portal Users
  100. Personalization of E-newsletters Based on Web Log Analysis and Clustering
  101. Data mining for business applications
  102. Improving SVM-Linear Predictions Using CART for Example Selection
  103. Selecting parameters of SVM using meta-learning and kernel matrix-based meta-features
  104. A WEIGHTED RANK MEASURE OF CORRELATION
  105. Monitoring the Quality of Meta-data in Web Portals Using Statistics, Visualization and Data Mining
  106. A Meta-Learning Method to Select the Kernel Width in Support Vector Regression
  107. Is the UCI Repository Useful for Data Mining?
  108. A Comparative Study of Some Issues Concerning Algorithm Recommendation Using Ranking Methods
  109. Improved Dataset Characterisation for Meta-learning
  110. Reducing Rankings of Classifiers by Eliminating Redundant Classifiers
  111. Sampling-Based Relative Landmarks: Systematically Test-Driving Algorithms before Choosing
  112. A Comparison of Ranking Methods for Classification Algorithm Selection
  113. Zoomed Ranking: Selection of Classification Algorithms Based on Relevant Performance Information
  114. Dynamic Discretization of Continuous Attributes
  115. Web Mining for the Integration of Data Mining with Business Intelligence in Web-Based Decision Support Systems
  116. Quantitative Evaluation of Clusterings for Marketing Applications: A Web Portal Case Study