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  1. Granular Nested Causal Complexes

    Causal reasoning occupies a central position in human reasoning. In many ways, causality is granular. This is true for: perception, commonsense...
    Lawrence J. Mazlack in Intelligent Data Mining
    Chapter
  2. Using an Adapted Classification Based on Associations Algorithm in an Activity-Based Transportation System

    A lot of research has been carried out in the past by using association rules to build more accurate classifiers. The idea behind these integrated...
    Davy Janssens, Geert Wets, ... Koen Vanhoof in Intelligent Data Mining
    Chapter
  3. The Evolution of the Concept of Fuzzy Measure

    Most information discovery processes need to understand the reasons of the success of the inference methods or the usability of the new information,...
    Luis Garmendia in Intelligent Data Mining
    Chapter
  4. Discovering the Factors Affecting the Location Selection of FDI in China*

    Since the late 1970s, Foreign Direct Investment (FDI) has played an important role in the economic development of China. However, the growth of FDI...
    Li Zhang, Yujie Zhu, ... Guoqing Chen in Intelligent Data Mining
    Chapter
  5. Sequential Pattern Mining*

    Sequential pattern discovery has emerged as an important research topic in knowledge discovery and data mining with broad applications. Previous...
    Tian-Rui Li, Yang Xu, ... Wu-ming Pan in Intelligent Data Mining
    Chapter
  6. Uncertain Knowledge Association Through Information Gain

    The problem of entity association is at the core of information mining techniques. In this work we propose an approach that links the similarity of...
    Athena Tocatlidou, Da Ruan, ... Nikos A. Lorentzos in Intelligent Data Mining
    Chapter
  7. Clustering Via Decision Tree Construction

    Clustering is an exploratory data analysis task. It aims to find the intrinsic structure of data by organizing data objects into similarity groups or...
    B. Liu, Y. **a, P.S. Yu in Foundations and Advances in Data Mining
    Chapter
  8. A New Theoretical Framework for K-Means-Type Clustering

    One of the fundamental clustering problems is to assign n points into k clusters based on the minimal sum-of-squares(MSSC), which is known to be...
    Chapter
  9. Intelligent Agents that Learn to Deliver Online Materials to Students Better: Agent Design, Simulation and Assumptions

    In this chapter, we discuss an integrated framework of case-based learning (CBL) in an agent that intelligently delivers learning materials to...
    Leen-Kiat Soh, Todd Blank, Lee Dee Miler in Knowledge-Based Virtual Education
    Chapter
  10. Integrated Clustering Modeling with Backpropagation Neural Network for Effcient Customer Relationship Management

    The rapid progress in digital data acquisition and storage technology has lead to the fast growing tremendous and amount of data stored in databases,...
    Tijen Ertay, Bora Çekyay in Intelligent Data Mining
    Chapter
  11. The Mathematics of Learning: Dealing with Data *

    Learning is key to develo** systems tailored to a broad range of data analysis and information extraction tasks. We outline the mathematical...
    Chapter
  12. Web Page Classification*

    This chapter describes systems that automatically classify web pages into meaningful categories. It first defines two types of web page...
    Chapter
  13. Sequential Pattern Mining by Pattern-Growth: Principles and Extensions*

    Sequential pattern mining is an important data mining problem with broad applications. However, it is also a challenging problem since the mining may...
    J. Han, J. Pei, X. Yan in Foundations and Advances in Data Mining
    Chapter
  14. Intelligent Agents to Improve Adaptivity in A Web-Based Learning Environment

    This chapter focuses on the use of intelligent agents in on-line learning environments in which educational organizations can equip students with...
    C. I. Peña, J. L. Marzo, J. Ll. de la Rosa in Knowledge-Based Virtual Education
    Chapter
  15. Homogeneous Semantics Preserving Deployments of Heterogeneous Networks of Embedded Systems

    Tagged systems provide a denotational semantics for embedded systems. A heterogeneous network of embedded systems can be modeled mathematically by a...
    Aaron D. Ames, Alberto Sangiovanni-Vincentelli, Shankar Sastry in Networked Embedded Sensing and Control
    Chapter
  16. Distributed Kalman Filtering and Sensor Fusion in Sensor Networks

    The problem of distributed Kalman filtering (DKF) for sensor networks is one of the most fundamental distributed estimation problems for scalable...
    Chapter
  17. Applications of Connectivity Graph Processes in Networked Sensing and Control

    This paper concerns the problem of controlling mobile nodes in a network in such a way that the resulting graph-encoding of the inter-node...
    Abubakr Muhammad, Meng Ji, Magnus Egerstedt in Networked Embedded Sensing and Control
    Chapter
  18. Delay-Reliability Tradeoffs in Wireless Networked Control Systems

    Networked control systems (NCS) require the data to be communicated timely and reliably. However, random transmission errors incurred by wireless...
    Min **e, Martin Haenggi in Networked Embedded Sensing and Control
    Chapter
  19. Plenary Talk: The Role of Information Theory in Communication Constrained Control Systems

    Communication is an important component of distributed, networked, and cooperative control systems. In most current systems the communication aspects...
    Chapter
  20. Simulation of Large-Scale Networked Control Systems Using GTSNetS

    This paper presents a simulation framework for distributed control using wireless sensor networks. The proposed framework is an extension of the...
    ElMoustapha Ould-Ahmed-Vall, Bonnie S. Heck, George F. Riley in Networked Embedded Sensing and Control
    Chapter
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