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Discovery science : 10th international conference, DS 2007, Sendai, Japan, October 1-4, 2007 ; proceedings

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Cover of 'Discovery science : 10th international conference, DS 2007, Sendai, Japan, October 1-4, 2007 ; proceedings'

Table of Contents

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    Book Overview
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    Chapter 1 Challenge for Info-plosion
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    Chapter 2 Machine Learning in Ecosystem Informatics
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    Chapter 3 Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity
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    Chapter 4 A Theory of Similarity Functions for Learning and Clustering
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    Chapter 5 A Hilbert Space Embedding for Distributions
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    Chapter 6 Time and Space Efficient Discovery of Maximal Geometric Graphs
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    Chapter 7 Iterative Reordering of Rules for Building Ensembles Without Relearning
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    Chapter 8 On Approximating Minimum Infrequent and Maximum Frequent Sets
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    Chapter 9 A Partially Dynamic Clustering Algorithm for Data Insertion and Removal
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    Chapter 10 Positivism Against Constructivism: A Network Game to Learn Epistemology
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    Chapter 11 Learning Locally Weighted C4.4 for Class Probability Estimation
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    Chapter 12 User Preference Modeling from Positive Contents for Personalized Recommendation
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    Chapter 13 Reducing Trials by Thinning-Out in Skill Discovery
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    Chapter 14 A Theoretical Study on Variable Ordering of Zero-Suppressed BDDs for Representing Frequent Itemsets
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    Chapter 15 Fast NML Computation for Naive Bayes Models
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    Chapter 16 Unsupervised Spam Detection Based on String Alienness Measures
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    Chapter 17 A Consequence Finding Approach for Full Clausal Abduction
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    Chapter 18 Literature-Based Discovery by an Enhanced Information Retrieval Model
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    Chapter 19 Discovering Mentorship Information from Author Collaboration Networks
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    Chapter 20 Active Contours as Knowledge Discovery Methods
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    Chapter 21 An Efficient Polynomial Delay Algorithm for Pseudo Frequent Itemset Mining
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    Chapter 22 Discovering Implicit Feedbacks from Search Engine Log Files
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    Chapter 23 Pharmacophore Knowledge Refinement Method in the Chemical Structure Space
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    Chapter 24 An Attempt to Rebuild C. Bernard’s Scientific Steps
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    Chapter 25 Semantic Annotation of Data Tables Using a Domain Ontology
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    Chapter 26 Model Selection and Estimation Via Subjective User Preferences
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    Chapter 27 Detecting Concept Drift Using Statistical Testing
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    Chapter 28 Towards Future Technology Projection: A Method for Extracting Capability Phrases from Documents
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    Chapter 29 Efficient Incremental Mining of Top-K Frequent Closed Itemsets
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    Chapter 30 An Intentional Kernel Function for RNA Classification
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    Chapter 31 Mining Subtrees with Frequent Occurrence of Similar Subtrees
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    Chapter 32 Semantic Based Real-Time Clustering for PubMed Literatures
Attention for Chapter 3: Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity
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Chapter title
Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity
Chapter number 3
Book title
Discovery Science
Published by
Springer, Berlin, Heidelberg, October 2007
DOI 10.1007/978-3-540-75488-6_3
Book ISBNs
978-3-54-075487-9, 978-3-54-075488-6
Authors

Jürgen Schmidhuber, Schmidhuber, Jürgen

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 1%
Unknown 99 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 2%
Professor 1 1%
Student > Bachelor 1 1%
Student > Master 1 1%
Professor > Associate Professor 1 1%
Other 0 0%
Unknown 94 94%
Readers by discipline Count As %
Computer Science 3 3%
Psychology 1 1%
Medicine and Dentistry 1 1%
Engineering 1 1%
Unknown 94 94%