New Frontiers in Mining Complex Patterns : First International Workshop, NFMCP 2012, Held in Conjunction with ECML/PKDD 2012, Bristol, UK, September 24, 2012, Revised Selected Papers / edited by Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew Ras.

Format:

Book

Contributor:

Appice, Annalisa, Editor.

Ceci, Michelangelo, Editor.

Loglisci, Corrado, Editor.

Manco, Giuseppe, Editor.

Masciari, Elio, Editor.

Raś, Zbigniew, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 7765

Lecture Notes in Artificial Intelligence, 2945-9141 ; 7765

Language:

English

Subjects (All):

Data mining.

Database management.

Information storage and retrieval systems.

Artificial intelligence.

Data Mining and Knowledge Discovery.

Database Management.

Information Storage and Retrieval.

Artificial Intelligence.

Local Subjects:

Data Mining and Knowledge Discovery.

Database Management.

Information Storage and Retrieval.

Artificial Intelligence.

Physical Description:

1 online resource (X, 231 pages) : 57 illustrations

Edition:

1st ed. 2013.

Contained In:

Springer Nature eBook

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.

System Details:

text file PDF

Summary:

This book constitutes the thoroughly refereed conference proceedings of the First International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2012, held in conjunction with ECML/PKDD 2012, in Bristol, UK, in September 2012. The 15 revised full papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on mining rich (relational) datasets, mining complex patterns from miscellaneous data, mining complex patterns from trajectory and sequence data, and mining complex patterns from graphs and networks.

Contents:

Learning with Configurable Operators and RL-Based Heuristics.- Reducing Examples in Relational Learning with Bounded-Treewidth Hypotheses.- Mining Complex Event Patterns in Computer Networks

Learning in the Presence of Large Fluctuations: A Study of Aggregation and Correlation

Machine Learning as an Objective Approach to Understanding Music.- Pair-Based Object-Driven Action Rules

Effectively Grouping Trajectory Streams.- Healthcare Trajectory Mining by Combining Multidimensional Component and Itemsets

Graph-Based Approaches to Clustering Network-Constrained Trajectory Data

Finding the Most Descriptive Substructures in Graphs with Discrete and Numeric Labels.- Learning in Probabilistic Graphs Exploiting Language-Constrained Patterns.- Improving Robustness and Flexibility of Concept Taxonomy Learning from Text.- Discovering Evolution Chains in Dynamic Networks.- Supporting Information Spread in a Social Internetworking Scenario.- Context-Aware Predictions on Business Processes: An Ensemble-Based Solution. Reducing Examples in Relational Learning with Bounded-Treewidth Hypotheses.- Mining Complex Event Patterns in Computer Networks

Finding the Most Descriptive Substructures in Graphs with Discrete and Numeric Labels.- Learning in Probabilistic Graphs Exploiting Language-Constrained Patterns.- Improving Robustness and Flexibility of Concept Taxonomy Learning from Text.- Discovering Evolution Chains in Dynamic Networks.- Supporting Information Spread in a Social Internetworking Scenario.- Context-Aware Predictions on Business Processes: An Ensemble-Based Solution. .

Other Format:

Printed edition:

ISBN:

978-3-642-37382-4

9783642373824

Access Restriction:

Restricted for use by site license.