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Discovery Science

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Inhalt Invited Papers.- Invention and Artificial Intelligence.- Algorithms and Software for Collaborative Discovery from Autonomou... Weiterlesen
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Beschreibung

Inhalt

Invited Papers.- Invention and Artificial Intelligence.- Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources.- Training Support Vector Machines via SMO-Type Decomposition Methods.- The Robot Scientist Project.- The Arrowsmith Project: 2005 Status Report.- Regular Contributions - Long Papers.- Practical Algorithms for Pattern Based Linear Regression.- Named Entity Recognition for the Indonesian Language: Combining Contextual, Morphological and Part-of-Speech Features into a Knowledge Engineering Approach.- Bias Management of Bayesian Network Classifiers.- A Bare Bones Approach to Literature-Based Discovery: An Analysis of the Raynaud's/Fish-Oil and Migraine-Magnesium Discoveries in Semantic Space.- Assisting Scientific Discovery with an Adaptive Problem Solver.- Cross-Language Mining for Acronyms and Their Completions from the Web.- Mining Frequent ?-Free Patterns in Large Databases.- An Experiment with Association Rules and Classification: Post-Bagging and Conviction.- Movement Analysis of Medaka (Oryzias Latipes) for an Insecticide Using Decision Tree.- Support Vector Inductive Logic Programming.- Measuring Over-Generalization in the Minimal Multiple Generalizations of Biosequences.- The q-Gram Distance for Ordered Unlabeled Trees.- Monotone Classification by Function Decomposition.- Learning On-Line Classification via Decorrelated LMS Algorithm: Application to Brain-Computer Interfaces.- An Algorithm for Mining Implicit Itemset Pairs Based on Differences of Correlations.- Pattern Classification via Single Spheres.- SCALETRACK: A System to Discover Dynamic Law Equations Containing Hidden States and Chaos.- Exploring Predicate-Argument Relations for Named Entity Recognition in the Molecular Biology Domain.- Massive Biomedical Term Discovery.- Active Constrained Clustering by Examining Spectral Eigenvectors.- Learning Ontology-Aware Classifiers.- Regular Contributions - Regular Papers.- Automatic Extraction of Proteins and Their Interactions from Biological Text.- A Data Analysis Approach for Evaluating the Behavior of Interestingness Measures.- Unit Volume Based Distributed Clustering Using Probabilistic Mixture Model.- Finding Significant Web Pages with Lower Ranks by Pseudo-Clique Search.- CLASSIC'CL: An Integrated ILP System.- Detecting and Revising Misclassifications Using ILP.- Project Reports.- Self-generation of Control Rules Using Hierarchical and Nonhierarchical Clustering for Coagulant Control of Water Treatment Plants.- A Semantic Enrichment of Data Tables Applied to Food Risk Assessment.- Knowledge Discovery Through Composited Visualization, Navigation and Retrieval.- A Tabu Clustering Method with DHB Operation and Mergence and Partition Operation.- Discovering User Preferences by Using Time Entries in Click-Through Data to Improve Search Engine Results.- Network Boosting for BCI Applications.- Rule-Based FCM: A Relational Mapping Model.- Effective Classifier Pruning with Rule Information.- Text Mining for Clinical Chinese Herbal Medical Knowledge Discovery.

Produktinformationen

Titel: Discovery Science
Untertitel: 8th International Conference, DS 2005, Singapore, October 8-11, 2005, Proceedings
Editor:
EAN: 9783540316985
Digitaler Kopierschutz: Wasserzeichen
Format: E-Book (pdf)
Hersteller: Springer Berlin Heidelberg
Genre: Philosophie
Anzahl Seiten: 404
Veröffentlichung: 24.10.2005
Dateigrösse: 6.5 MB

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