
Seriation in Combinatorial and Statistical Data Analysis by Isral Lerman
This monograph offers an original broad and very diverse exploration of the seriation domain in data analysis, together with building a specific relation to clustering.Relative to a data table crossing a set of objects and a set of descriptive attributes, the search for orders which correspond respectively to these two sets is formalized mathematically and statistically.
State-of-the-art methods are created and compared with classical methods and a thorough understanding of the mutual relationships between these methods is clearly expressed. The authors distinguish two families of methods:
- Geometric representation methods
- Algorithmic and Combinatorial methods
Original and accurate methods are provided in the framework for both families. Their basis and comparison is made on both theoretical and experimental levels. The experimental analysis is very varied and very comprehensive. Seriation in Combinatorial and Statistical Data Analysis has a unique character in the literature falling within the fields of Data Analysis, Data Mining and Knowledge Discovery. It will be a valuable resource for students and researchers in the latter fields.
-
Game Theoretic Problems in Network Economics and Mechanism Design Solutions
-
Ontological Engineering
-
Mining Software Engineering Data for Software Reuse
-
R-Trees: Theory and Applications
-
Intelligence Management
-
Secure Information Management Using Linguistic Threshold Approach
-
Hierarchical Feature Selection for Knowledge Discovery
-
Developing Multi-Database Mining Applications
-
Uncertainty Handling and Quality Assessment in Data Mining
-
Knowledge Discovery in Multiple Databases
-
Meta-Programming and Model-Driven Meta-Program Development
-
Smart Systems for E-Health
-
Trends in Interactive Visualization
-
Business Intelligence and Performance Management
-
Privacy and Anonymity in Information Management Systems
-
Scientific Data Analysis using Jython Scripting and Java
-
Adaptive Resonance Theory in Social Media Data Clustering
-
Agent-Based Service-Oriented Computing
-
Knowledge Processing with Interval and Soft Computing
-
Learning Representation for Multi-View Data Analysis
-
Data Mining with Computational Intelligence
-
Creating Web-based Laboratories
-
Data Complexity in Pattern Recognition
-
Representation and Management of Narrative Information
-
Emergent Web Intelligence: Advanced Information Retrieval
-
Machine Learning and Data Mining for Computer Security
-
Data Mining for Social Robotics
-
Convergence and Knowledge Processing in Multi-Agent Systems
-
Artificial Intelligence and Economic Theory: Skynet in the Market
-
Advanced Methods for Knowledge Discovery from Complex Data
-
Understanding Information
-
Robust Representation for Data Analytics
-
Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering
Teacher-researcher in Applied Mathematics and Computer Science, Henri Leredde worked as a member of the Mathematics department at Sorbonne Paris Nord University. He was Director of Studies for the "Telecom and Networks" part of the Sup Galilée engineering school. He is now an associate researcher at LAGA(1). In addition, he is an archaeologist, specialist in Gallo-Roman pottery and also practices numerous aerial surveys in archeology as a pilot.
(1) - LAGA : Laboratoire Analyse, Géométrie et Applications, CNRS UMR 7539 and Department of Mathematics, Institut Galilée, Sorbonne Paris-Nord University.
| SKU | Unavailable |
| ISBN 13 | 9783030926960 |
| ISBN 10 | 3030926966 |
| Title | Seriation in Combinatorial and Statistical Data Analysis |
| Author | Isral Lerman |
| Series | Advanced Information And Knowledge Processing |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer Nature Switzerland AG |
| Year published | 2023-03-06 |
| Number of pages | 277 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |
































