Discovery Science de Vincent Corruble

Discovery Science

Vincent Corruble

Masayuki Takeda

Einoshin Suzuki

en Limba Engleză Paperback – 17 sep 2007

This volume contains the papers presented at DS-2007:The Tenth International Conference on Discovery Science held in Sendai, Japan, October 1–4, 2007. The main objective of the Discovery Science (DS) conference series is to p- vide an open forum for intensive discussions and the exchange of new ideas and information among researchers working in the area of automating scienti?c d- covery or working on tools for supporting the human process of discovery 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). ThiscombinationofALTandDSallowsforacomprehensivetreatmentof the whole range, from theoretical investigations to practical applications. C- tinuing this tradition, DS 2007 was co-located with the 18th ALT conference (ALT 2007). The proceedings of ALT 2007 were published as a twin volume 4754 of the LNCS series. The International Steering Committee of the Discovery Science conference series provided important advice on a number of issues during the planning of Discovery Science 2007. The members of the Steering Committee are Einoshin Suzuki (Kyushu University, Chair), Achim G.

Citește tot Restrânge

Cuprins

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 StatisticalTesting.- 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.