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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... -
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... -
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,... -
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... -
Sequential Pattern Mining*
Sequential pattern discovery has emerged as an important research topic in knowledge discovery and data mining with broad applications. Previous... -
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... -
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... -
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... -
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... -
9 On Observing Contact States in Overconstrained Manipulation
Estimation of contact state is important to any multi-point interaction that involves frictional stick/slip phenomena. In particular, when there are... -
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,... -
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... -
Web Page Classification*
This chapter describes systems that automatically classify web pages into meaningful categories. It first defines two types of web page... -
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... -
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... -
13 Haptic Interfaces: Collocation and Coherence Issues
Multi-modality, collocation and immersive VE nowadays represents the break-trough barrier of human computer interaction. Typical VE systems... -
6 Efficient and Precise Grasp Planning for Real World Objects
With the development of .exible and highly integrated dexterous grip** devices (e.g. fig.6.1) the research results on grasp and manipulation... -
4 Modelling and Controlling the Compliance of a Robotic Hand with Soft Finger-pads
Compliant pads greatly contribute to increase the robustness and the stability of grasps of robot hands, because of their conformability to the... -
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... -
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...