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  1. On Statistical Independence in a Contingency Table

    This paper gives a proof showing that statistical independence in a contingency table is a special type of linear independence, where the rank of a...
    Shusaku Tsumoto in Foundations of Data Mining and knowledge Discovery
    Chapter

  2. First-Order Logic Based Formalism for Temporal Data Mining*

    In this article we define a formalism for a methodology that has as purpose the discovery of knowledge, represented in the form of general Horn...
    Paul Cotofrei, Kilian Stoffel in Foundations of Data Mining and knowledge Discovery
    Chapter

  3. A Probabilistic Logic-based Framework for Characterizing Knowledge Discovery in Databases

    In order to further improve the KDD process in terms of both the degree of automation achieved and types of knowledge discovered, we argue that a...
    Ying Xie, Vijay V. Raghavan in Foundations of Data Mining and knowledge Discovery
    Chapter

  4. Cluster Identification Using Maximum Configuration Entropy

    Clustering is an important task in data mining and machine learning. In this paper, a normalized graph sampling algorithm for clustering that...
    C.H. Li in Foundations of Data Mining and knowledge Discovery
    Chapter

  5. Identification of Critical Values in Latent Semantic Indexing

    In this chapter we analyze the values used by Latent Semantic Indexing (LSI) for information retrieval. By manipulating the values in the Singular...
    April Kontostathis, William M. Pottenger, Brian D. Davison in Foundations of Data Mining and knowledge Discovery
    Chapter

  6. An Algorithm to Calculate the Expected Value of an Ongoing User Session

    The fiercely competitive web-based electronic commerce environment has made necessary the application of intelligent methods to gather and analyze...
    S. Millán, E. Menasalvas, ... E. Hochsztain in Foundations of Data Mining and knowledge Discovery
    Chapter

  7. Justification and Hypothesis Selection in Data Mining

    Data mining is an instance of the inductive methodology. Many philosophical considerations for induction can also be carried out for data mining. In...
    Tuan-Fang Fan, Duen-Ren Liu, Churn-Jung Liau in Foundations of Data Mining and knowledge Discovery
    Chapter

  8. Direct Products of Fuzzy Subgroups and Fuzzy Cyclic Subgroups

    In Chapter 6, a necessary and sufficient condition for a fuzzy subgroup to be a weak direct sum of fuzzy subgroups was obtained by employing known...
    John N. Mordeson, Kiran R. Bhutani, Azriel Rosenfeld in Fuzzy Group Theory
    Chapter

  9. Synchronization in Complex Networks

    The study of complex systems pervades all of science, from cell biology to ecology, from computer science to meteorology. A paradigm of a complex...
    Ljupco Kocarev, Gábor Vattay in Complex Dynamics in Communication Networks
    Chapter

  10. Data Traffic, Topology and Congestion

    We consider the interaction between the topology of a network and the tra.c carried along its channels. The binding elements between the topology and...
    David K. Arrowsmith, R.J. Mondrag, M. Woolf in Complex Dynamics in Communication Networks
    Chapter

  11. Cancer Diagnosis and Protein Secondary Structure Prediction Using Support Vector Machines

    In this chapter, we use support vector machines (SVMs) to deal with two bioinformatics problems, i.e., cancer diagnosis based on gene expression data...
    F. Chu, G. Jin, L. Wang in Support Vector Machines: Theory and Applications
    Chapter

  12. Application of Support Vector Machines in Inverse Problems in Ocean Color Remote Sensing

    Neural networks are widely used as transfer functions in inverse problems in remote sensing. However, this method still suffers from some problems...
    H. Zhan in Support Vector Machines: Theory and Applications
    Chapter

  13. Gas Sensing Using Support Vector Machines

    In this chapter we deal with the use of Support Vector Machines in gas sensing. After a brief introduction to the inner workings of multisensor...
    J. Brezmes, E. Llobet, ... J.W. Gardner in Support Vector Machines: Theory and Applications
    Chapter

  14. Improving the Performance of the Support Vector Machine: Two Geometrical Scaling Methods

    In this chapter, we discuss two possible ways of improving the performance of the SVM, using geometric methods. The first adapts the kernel by...
    P. Williams, S. Wu, J. Feng in Support Vector Machines: Theory and Applications
    Chapter

  15. Linkage Learning Genetic Algorithm

    In order to handle linkage evolution and to tackle the ordering problem, Harik [47] took Holland’s call [53] for the evolution of tight linkage quite...
    Ying-ping Chen in Extending the Scalability of Linkage Learning Genetic Algorithms
    Chapter

  16. Introduction

    Genetic algorithms (GAs) are powerful search techniques based on principles of evolution. They are now widely applied to solve problems in many...
    Ying-ping Chen in Extending the Scalability of Linkage Learning Genetic Algorithms
    Chapter

  17. Preliminaries: Assumptions and the Test Problem

    After introducing the background and motivation of the linkage learning genetic algorithm, we will start to improve and understand the linkage...
    Ying-ping Chen in Extending the Scalability of Linkage Learning Genetic Algorithms
    Chapter

  18. INTRODUCTION

    Over the last decade, a series of publications has brought and established new research areas related to music, and intensified the research verging...
    Bożena Kostek in Perception-Based Data Processing in Acoustics
    Chapter

  19. PERCEPTUAL BASES OF HEARING AND MUSIC PERCEPTION

    The human auditory system pertains to the entire peripheral auditory mechanism. Classically, the peripheral auditory system has been divided into...
    Bożena Kostek in Perception-Based Data Processing in Acoustics
    Chapter

  20. INTELLIGENT MUSICAL INSTRUMENT SOUND CLASSIFICATION

    This chapter is devoted to intelligent classification of the sound of musical instruments. Although it is possible, and in some applications...
    Bożena Kostek in Perception-Based Data Processing in Acoustics
    Chapter