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.
Author(s): Masaru Kitsuregawa (auth.), Vincent Corruble, Masayuki Takeda, Einoshin Suzuki (eds.)
Series: Lecture Notes in Computer Science 4755 : Lecture Notes in Artificial Intelligence
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2007
Language: English
Pages: 300
Tags: Artificial Intelligence (incl. Robotics); Database Management; Information Storage and Retrieval; Computer Appl. in Administrative Data Processing; Computer Appl. in Social and Behavioral Sciences
Front Matter....Pages -
Challenge for Info-plosion....Pages 1-8
Machine Learning in Ecosystem Informatics....Pages 9-25
Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity....Pages 26-38
A Theory of Similarity Functions for Learning and Clustering....Pages 39-39
A Hilbert Space Embedding for Distributions....Pages 40-41
Time and Space Efficient Discovery of Maximal Geometric Graphs....Pages 42-55
Iterative Reordering of Rules for Building Ensembles Without Relearning....Pages 56-67
On Approximating Minimum Infrequent and Maximum Frequent Sets....Pages 68-77
A Partially Dynamic Clustering Algorithm for Data Insertion and Removal....Pages 78-90
Positivism Against Constructivism: A Network Game to Learn Epistemology....Pages 91-103
Learning Locally Weighted C4.4 for Class Probability Estimation....Pages 104-115
User Preference Modeling from Positive Contents for Personalized Recommendation....Pages 116-126
Reducing Trials by Thinning-Out in Skill Discovery....Pages 127-138
A Theoretical Study on Variable Ordering of Zero-Suppressed BDDs for Representing Frequent Itemsets....Pages 139-150
Fast NML Computation for Naive Bayes Models....Pages 151-160
Unsupervised Spam Detection Based on String Alienness Measures....Pages 161-172
A Consequence Finding Approach for Full Clausal Abduction....Pages 173-184
Literature-Based Discovery by an Enhanced Information Retrieval Model....Pages 185-196
Discovering Mentorship Information from Author Collaboration Networks....Pages 197-208
Active Contours as Knowledge Discovery Methods....Pages 209-218
An Efficient Polynomial Delay Algorithm for Pseudo Frequent Itemset Mining....Pages 219-230
Discovering Implicit Feedbacks from Search Engine Log Files....Pages 231-242
Pharmacophore Knowledge Refinement Method in the Chemical Structure Space....Pages 243-247
An Attempt to Rebuild C. Bernard’s Scientific Steps....Pages 248-252
Semantic Annotation of Data Tables Using a Domain Ontology....Pages 253-258
Model Selection and Estimation Via Subjective User Preferences....Pages 259-263
Detecting Concept Drift Using Statistical Testing....Pages 264-269
Towards Future Technology Projection: A Method for Extracting Capability Phrases from Documents....Pages 270-274
Efficient Incremental Mining of Top-K Frequent Closed Itemsets....Pages 275-280
An Intentional Kernel Function for RNA Classification....Pages 281-285
Mining Subtrees with Frequent Occurrence of Similar Subtrees....Pages 286-290
Semantic Based Real-Time Clustering for PubMed Literatures....Pages 291-295
Back Matter....Pages -
