Invited Papers -- Challenge for Info-plosion -- Machine Learning in Ecosystem Informatics -- Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity -- A Theory of Similarity Functions for Learning and Clustering -- A Hilbert Space Embedding for Distributions -- Long Papers -- Time and Space Efficient Discovery of Maximal Geometric Graphs -- Iterative Reordering of Rules for Building Ensembles Without Relearning -- On Approximating Minimum Infrequent and Maximum Frequent Sets -- A Partially Dynamic Clustering Algorithm for Data Insertion and Removal -- Positivism Against Constructivism: A Network Game to Learn Epistemology -- Learning Locally Weighted C4.4 for Class Probability Estimation -- User Preference Modeling from Positive Contents for Personalized Recommendation -- Reducing Trials by Thinning-Out in Skill Discovery -- A Theoretical Study on Variable Ordering of Zero-Suppressed BDDs for Representing Frequent Itemsets -- Fast NML Computation for Naive Bayes Models -- Unsupervised Spam Detection Based on String Alienness Measures -- A Consequence Finding Approach for Full Clausal Abduction -- Literature-Based Discovery by an Enhanced Information Retrieval Model -- Discovering Mentorship Information from Author Collaboration Networks -- Active Contours as Knowledge Discovery Methods -- An Efficient Polynomial Delay Algorithm for Pseudo Frequent Itemset Mining -- Discovering Implicit Feedbacks from Search Engine Log Files -- Regular Papers -- Pharmacophore Knowledge Refinement Method in the Chemical Structure Space -- An Attempt to Rebuild C. Bernard’s Scientific Steps -- Semantic Annotation of Data Tables Using a Domain Ontology -- Model Selection and Estimation Via Subjective User Preferences -- Detecting Concept Drift Using Statistical Testing -- Towards Future Technology Projection: A Method for Extracting Capability Phrases from Documents -- Efficient Incremental Mining of Top-K Frequent Closed Itemsets -- An Intentional Kernel Function for RNA Classification -- Mining Subtrees with Frequent Occurrence of Similar Subtrees -- Semantic Based Real-Time Clustering for PubMed Literatures.