th This volume contains the papers presented at the 13 International Conference on Discovery Science (DS 2010) held in Canberra, Australia, October 6 8, 2010. The main objective of the Discovery Science (DS) conference series is to provide an open forum for intensive discussions and the exchange of new ideas and information among researchers working in the area of automating sci- ti?c discovery or working on tools for supporting the human process of disc- ery in science. It has been a successful arrangement in the past to co-locate the DS conference with the International Conference on Algorithmic Learning Theory (ALT). This combination of ALT and DS allows for a comprehensive treatment of the whole range, from theoretical investigations to practical app- cations. Continuing in this tradition, DS 2010 was co-located with the 21st ALT conference (ALT 2010). The proceedings of ALT 2010 were published as a twin volume (6331) of the LNCS series. The international steering committee of the Discovery Science conference - ries providedimportantadvice on a number of issues during the planning of D- coveryScience2010. ThemembersofthesteeringcommitteewereAlbertoAp- tolico, Setsuo Arikawa, Hiroki Arimura, Jean-Francois Boulicaut, Vitor Santos Costa, Vincent Corruble, Joao Gama, Achim Ho?mann, Tamas Horvath, Alipio Jorge, Hiroshi Motoda, Ayumi Shinohara, Einoshin Suzuki (Chair), Masayuki Takeda, Akihiro Yamamoto, and Thomas Zeugmann. We received 43 full-paper submissions out of which 25 long papers were - cepted for presentation and are published in this volume.

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Inhalt
Sentiment Knowledge Discovery in Twitter Streaming Data.- A Similarity-Based Adaptation of Naive Bayes for Label Ranking: Application to the Metalearning Problem of Algorithm Recommendation.- Topology Preserving SOM with Transductive Confidence Machine.- An Artificial Experimenter for Enzymatic Response Characterisation.- Subgroup Discovery for Election Analysis: A Case Study in Descriptive Data Mining.- On Enumerating Frequent Closed Patterns with Key in Multi-relational Data.- Why Text Segment Classification Based on Part of Speech Feature Selection.- Speeding Up and Boosting Diverse Density Learning.- Incremental Learning of Cellular Automata for Parallel Recognition of Formal Languages.- Sparse Substring Pattern Set Discovery Using Linear Programming Boosting.- Discovery of Super-Mediators of Information Diffusion in Social Networks.- Integer Linear Programming Models for Constrained Clustering.- Efficient Visualization of Document Streams.- Bridging Conjunctive and Disjunctive Search Spaces for Mining a New Concise and Exact Representation of Correlated Patterns.- Graph Classification Based on Optimizing Graph Spectra.- Algorithm for Detecting Significant Locations from Raw GPS Data.- Discovery of Conservation Laws via Matrix Search.- Gaussian Clusters and Noise: An Approach Based on the Minimum Description Length Principle.- Exploiting Code Redundancies in ECOC.- Concept Convergence in Empirical Domains.- Equation Discovery for Model Identification in Respiratory Mechanics of the Mechanically Ventilated Human Lung.- Mining Class-Correlated Patterns for Sequence Labeling.- ESTATE: Strategy for Exploring Labeled Spatial Datasets Using Association Analysis.- Adapted Transfer of Distance Measures for Quantitative Structure-Activity Relationships.- Incremental Mining of Closed Frequent Subtrees.- Optimal Online Prediction in Adversarial Environments.- Discovery of Abstract Concepts by a Robot.- Contrast Pattern Mining and Its Application for Building Robust Classifiers.- Towards General Algorithms for Grammatical Inference.- The Blessing and the Curse of the Multiplicative Updates.