Discovery Science : 15th International Conference, DS 2012, Lyon, France, October 29-31, 2012, Proceedings / edited by Jean-Gabriel Ganascia, Philippe Lenca, Jean-Marc Petit.

Format:

Book

Contributor:

Ganascia, Jean-Gabriel, editor.

Lenca, Philippe, editor.

Petit, Jean-Marc, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 7569.

Lecture Notes in Artificial Intelligence ; 7569

Language:

English

Subjects (All):

Artificial intelligence.

Information storage and retrieval.

Application software.

Database management.

Data mining.

Algorithms.

Artificial Intelligence.

Information Storage and Retrieval.

Information Systems Applications (incl. Internet).

Database Management.

Data Mining and Knowledge Discovery.

Algorithm Analysis and Problem Complexity.

Local Subjects:

Artificial Intelligence.

Information Storage and Retrieval.

Information Systems Applications (incl. Internet).

Database Management.

Data Mining and Knowledge Discovery.

Algorithm Analysis and Problem Complexity.

Physical Description:

1 online resource (XIV, 329 pages) : 77 illustrations.

Edition:

First edition 2012.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.

System Details:

text file PDF

Summary:

This book constitutes the refereed proceedings of the 15th International Conference on Discovery Science, DS 2012, held in Lyon, France, in October 2012. The 22 papers presented in this volume were carefully reviewed and selected from 46 submissions. The field of discovery science aims at inducing and validating new scientific hypotheses from data. The scope of this conference includes the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis, theory of learning, tools for supporting the human process of discovery in science, as well as their application to knowledge discovery.

Contents:

Declarative Modeling for Machine Learning and Data Mining

Recent Developments in Pattern Mining

Exploring Sequential Data

Large Scale Spectral Clustering Using Resistance Distance and Spielman-Teng Solvers

Prediction of Quantiles by Statistical Learning and Application to GDP Forecasting

Policy Search in a Space of Simple Closed-form Formulas: Towards Interpretability of Reinforcement Learning

Towards Finding Relational Redescriptions

Descriptive Modeling of Systemic Banking Crises

A Trim Distance between Positions in Nucleotide Sequences

Data Squashing for HSV Subimages by an Autonomous Mobile Robot

Cohesive Co-evolution Patterns in Dynamic Attributed Graphs

Efficient Redundancy Reduced Subgroup Discovery via Quadratic Programming

HCAC: Semi-supervised Hierarchical Clustering Using Confidence- Based Active Learning

LF-CARS: A Loose Fragment-Based Consensus Clustering Algorithm with a Robust Similarity

Fast Approximation Algorithm for the 1-Median Problem

Online Co-regularized Algorithms

Fast Progressive Training of Mixture Models for Model Selection

Including Spatial Relations and Scales within Sequential Pattern Extraction

Predicting Ramp Events with a Stream-Based HMM Framework

Burst Detection in a Sequence of Tweets Based on Information Diffusion Model

Error-Correcting Output Codes as a Transformation from Multi-Class to Multi-Label Prediction

An Assessment on Loan Performance from Combined Quantitative and Qualitative Data in XML

Structural Change Pattern Mining Based on Constrained Maximal k-Plex Search

Enhancing Patent Expertise through Automatic Matching with Scientific Papers

Soft Threshold Constraints for Pattern Mining.

Other Format:

Printed edition:

ISBN:

978-3-642-33492-4

9783642334924

Access Restriction:

Restricted for use by site license.