Discovery science : 7th international conference, DS 2004, Padova, Italy, October 2 5, 2004 : proceedings
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Author: DS 2004 (2004 : Padua, Italy), Suzuki, Einoshin, Arikawa, S. (Setsuo), 1941-
Added by: sketch
Added Date: 2015-12-29
Language: eng
Subjects: Discoveries in science, Research, Science
Publishers: Berlin ; New York : Springer
Collections: folkscanomy miscellaneous, folkscanomy, additional collections
ISBN Number: 3540233571
Pages Count: 300
PPI Count: 300
PDF Count: 1
Total Size: 225.05 MB
PDF Size: 5.55 MB
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Discovery Science: 7th International Conference, DS 2004, Padova, Italy, October 2-5, 2004. Proceedings
Author: Einoshin Suzuki, Setsuo Arikawa
Published by Springer Berlin Heidelberg
ISBN: 978-3-540-23357-2
DOI: 10.1007/b100845
Table of Contents:
Includes bibliographical references and index
Author: Einoshin Suzuki, Setsuo Arikawa
Published by Springer Berlin Heidelberg
ISBN: 978-3-540-23357-2
DOI: 10.1007/b100845
Table of Contents:
- Predictive Graph Mining
- An Efficient Algorithm for Enumerating Closed Patterns in Transaction Databases
- Finding Optimal Pairs of Cooperative and Competing Patterns with Bounded Distance
- Mining Noisy Data Streams via a Discriminative Model
- CorClass: Correlated Association Rule Mining for Classification
- Maximum a Posteriori Tree Augmented Naive Bayes Classifiers
- Improving Prediction of Distance-Based Outliers
- Detecting Outliers via Logical Theories and Its Data Complexity
- Fast Hierarchical Clustering Algorithm Using Locality-Sensitive Hashing
- Measuring the Similarity for Heterogenous Data: An Ordered Probability-Based Approach
- Constructive Inductive Learning Based on Meta-attributes
- Resemblance Coefficient and a Quantum Genetic Algorithm for Feature Selection
- Extracting Positive Attributions from Scientific Papers
- Enhancing SVM with Visualization
- An Associative Information Retrieval Based on the Dependency of Term Co-occurrence
- On the Convergence of Incremental Knowledge Base Construction
- Privacy Problems with Anonymized Transaction Databases
- A Methodology for Biologically Relevant Pattern Discovery from Gene Expression Data
- Using the Computer to Study the Dynamics of the Handwriting Processes
- Product Recommendation in e-Commerce Using Direct and Indirect Confidence for Historical User Sessions
Includes bibliographical references and index
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