Discovery Science

Mixture Models from Multiresolution 0-1 Data.- Model Tree Ensembles for Modeling Dynamic Systems.- Fast and Scalable Image Retrieval Using Predictive Clustering Trees.- Avoiding Anomalies in Data Stream Learning.- Generalizing from Example Clusters.- Clustering Based Active Learning for Evolving Data Streams.- Robust Crowd Labeling Using Little Expertise.- A New Approach to String Pattern Mining with Approximate Match.- OntoDM-KDD: Ontology for Representing the Knowledge Discovery Process.- A Wordification Approach to Relational Data Mining.- Multi-interval Discretization of Continuous Attributes for Label Ranking.- Identifying Super-Mediators of Information Diffusion in Social Networks.- SM2D: A Modular Knowledge Discovery Approach Applied to Hydrological Forecasting.- A Dynamic Programming Algorithm for Learning Chain Event Graphs.- Mining Interesting Patterns in Multi-relational Data with N-ary Relationships.- Learning Hierarchical Multi-label Classification Trees from Network Data.- A Density-Based Backward Approach to Isolate Rare Events in Large-Scale Applications.- Inductive Process Modeling of Rab5-Rab7 Conversion in Endocytosis.- Fast Compression of Large-Scale Hypergraphs for Solving Combinatorial Problems.- Semantic Data Mining of Financial News Articles.- Polynomial Delay and Space Discovery of Connected and Acyclic Sub-hypergraphs in a Hypergraph.- Hyperlink Prediction in Hypernetworks Using Latent Social Features.- Extracting Opinionated (Sub)Features from a Stream of Product Reviews.