Machine Learning: Concepts, Methodologies, Tools and Applications

Fundamental Concepts and Theories

Chapter 1

A Comparison of Human and Computer Information Processing (pages 1-12)

Brian Whitworth, Hokyoung Ryu

Over 30 years ago, TV shows from The Jetsons to Star Trek suggested that by the millennium’s end computers would read, talk, recognize, walk, converse, think, and maybe even feel. People do these things easily, so how hard could it...

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Chapter 2

Machine Learning (pages 13-22)

João Gama, André C.P.L.F. de Carvalho

Machine learning techniques have been successfully applied to several real world problems in areas as diverse as image analysis, Semantic Web, bioinformatics, text processing, natural language processing,telecommunications, finance...

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Chapter 3

Machine Learning Through Data Mining (pages 23-31)

Diego Liberati

In dealing with information it often turns out that one has to face a huge amount of data, often not completely homogeneous and often without an immediate grasp of an underlying simple structure. Many records, each one instantiating...

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Chapter 4

Calibration of Machine Learning Models (pages 32-49)

Antonio Bella, Cèsar Ferri, José Hernández-Orallo, María José Ramírez-Quintana

The evaluation of machine learning models is a crucial step before their application because it is essential to assess how well a model will behave for every single case. In many real applications, not only is it important to know...

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Chapter 5

Classification of Web Pages Using Machine Learning Techniques (pages 50-65)

K. Selvakuberan, M. Indra Devi, R. Rajaram

The explosive growth of the Web makes it a very useful information resource to all types of users. Today, everyone accesses the Internet for various purposes and retrieving the required information within the stipulated time is the...

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Chapter 6

3D Modelling and Artificial Intelligence: A Descriptive Overview (pages 66-76)

G. N. Marichal, A. Hernández, E. J. González, L. Acosta, J. L. Saorin

This paper explains the different interactions between the Artificial Intelligence (AI) techniques and 3D modelling, not only the wide-used application of AI in order to the implementation of 3D environments, but the less explored...

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Chapter 7

An Overview of Knowledge Translation (pages 77-86)

Chris Groeneboer, Monika Whitney

Knowledge translation (KT) was traditionally framed as a problem of moving research results into policy and practice. The impetus for the flow of knowledge originated with researchers constructing new knowledge and seeing its...

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Chapter 8

Adaptive Technology and Its Applications (pages 87-96)

João José Neto

Before the advent of software engineering, the lack of memory space in computers and the absence of established programming methodologies led early programmers to use self-modification as a regular coding strategy. Although...

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Chapter 9

Adaptive Algorithms for Intelligent Geometric Computing (pages 97-104)

M. L. Gavrilova

This chapter spans topics from such important areas as Artificial Intelligence, Computational Geometry and Biometric Technologies. The primary focus is on the proposed Adaptive Computation Paradigm and its applications to surface...

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Chapter 10

Different Roles and Definitions of Spatial Data Fusion (pages 105-111)

Patrik Skogster

Geographic information is created by manipulating geographic (or spatial) data (generally known by the abbreviation geodata) in a computerized system. Geo-spatial information and geomatics are issues of modern business and research....

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Development and Design Methodologies

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Chapter 11

Machine Learning as a Commonsense Reasoning Process (pages 113-119)

Xenia Naidenova

One of the most important tasks in database technology is to combine the following activities: data mining or inferring knowledge from data and query processing or reasoning on acquired knowledge. The solution of this task requires a...

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Chapter 12

Motivated Learning for Computational Intelligence (pages 120-146)

Janusz A. Starzyk

This chapter describes a motivated learning (ML) method that advances model building and learning techniques required for intelligent systems. Motivated learning addresses critical limitations of reinforcement learning (RL), the more...

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Chapter 13

Designing a Computational Model of Learning (pages 147-174)

David Gibson

What would a game or simulation need to have in order to teach a teacher how people learn? This chapter uses a four-part framework of knowledge, learner, assessment, and community (Bransford et al., 2000) to discuss design...

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Chapter 14

Intelligent MAS in System Engineering and Robotics (pages 175-182)

G. Nicolás Marichal, Evelio J. González

The concept of agent has been successfully used in a wide range of applications such as Robotics, e-commerce, agent-assisted user training, military transport or health-care. The origin of this concept can be located in 1977, when...

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Chapter 15

Information Hiding by Machine Learning: A Method of Key Generation for Information Extracting Using Neural Network (pages 183-210)

Kensuke Naoe, Hideyasu Sasaki, Yoshiyasu Takefuji

In this paper, the authors propose information hiding by machine learning: a method of key generation for information extracting using neural network. The method consists of three layers for information hiding. First, the proposed...

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Chapter 16

Rule Engines and Agent-Based Systems (pages 211-218)

Agostino Poggi, Michele Tomaiuolo

Expert systems are successfully applied to a number of domains. Often built on generic rule-based systems, they can also exploit optimized algorithms. On the other side, being based on loosely coupled components and peer to peer...

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Chapter 17

Higher Order Neural Network Architectures for Agent-Based Computational Economics and Finance (pages 219-233)

John Seiffertt, Donald C. Wunsch II

As the study of agent-based computational economics and finance grows, so does the need for appropriate techniques for the modeling of complex dynamic systems and the intelligence of the constructive agent. These methods are...

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Chapter 18

A Bayesian Based Machine Learning Application to Task Analysis (pages 234-242)

Shu-Chiang Lin

Many task analysis techniques and methods have been developed over the past decades, but identifying and decomposing a user’s task into small task components remains a difficult, impractically time-consuming, and expensive process...

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Chapter 19

Combining Classifiers and Learning Mixture-of-Experts (pages 243-252)

Lei Xu, Shun-ichi Amari

Expert combination is a classic strategy that has been widely used in various problem solving tasks. A team of individuals with diverse and complementary skills tackle a task jointly such that a performance better than any single...

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Chapter 20

Designing Unsupervised Hierarchical Fuzzy Logic Systems (pages 253-261)

M. Mohammadian

Systems such as robotic systems and systems with large input-output data tend to be difficult to model using mathematical techniques. These systems have typically high dimensionality and have degrees of uncertainty in many...

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Chapter 21

A Self-Organizing Neural Network to Approach Novelty Detection (pages 262-282)

Marcelo Keese Albertini, Rodrigo Fernandes de Mello

Machine learning is a field of artificial intelligence which aims at developing techniques to automatically transfer human knowledge into analytical models. Recently, those techniques have been applied to time series with unknown...

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Chapter 22

Empirical Inference of Numerical Information into Causal Strategy Models by Means of Artificial Intelligence (pages 283-303)

Christian Hillbrand

The motivation for this chapter is the observation that many companies build their strategy upon poorly validated hypotheses about cause and effect of certain business variables. However, the soundness of these...

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Chapter 23

Designing Light Weight Intrusion Detection Systems: Non-negative Matrix Factorization Approach (pages 304-317)

Václav Snášel, Jan Platoš, Pavel Krömer, Ajith Abraham

Recently cyber security has emerged as an established discipline for computer systems and infrastructures with a focus on protection of valuable information stored on those systems from adversaries who want to obtain, corrupt...

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Chapter 24

A Multi-Agent Machine Learning Framework for Intelligent Energy Demand Management (pages 318-332)

Ying Guo, Rongxin Li

In order to cope with the unpredictability of the energy market and provide rapid response when supply is strained by demand, an emerging technology, called energy demand management, enables appliances to manage and defer their...

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Chapter 25

Modelling Gene Regulatory Networks Using Computational Intelligence Techniques (pages 333-352)

Ramesh Ram, Madhu Chetty

This chapter presents modelling gene regulatory networks (GRNs) using probabilistic causal model and the guided genetic algorithm. The problem of modelling is explained from both a biological and computational perspective. Further, a...

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Tools and Technologies

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Chapter 26

Application of Machine Learning Techniques to Predict Software Reliability (pages 354-370)

Ramakanta Mohanty, V. Ravi, M. R. Patra

In this paper, the authors employed machine learning techniques, specifically, Back propagation trained neural network (BPNN), Group method of data handling (GMDH), Counter propagation neural network (CPNN), Dynamic evolving...

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Chapter 27

Application of Artificial Immune Systems Paradigm for Developing Software Fault Prediction Models (pages 371-387)

Cagatay Catal, Soumya Banerjee

Artificial Immune Systems, a biologically inspired computing paradigm such as Artificial Neural Networks, Genetic Algorithms, and Swarm Intelligence, embody the principles and advantages of vertebrate immune systems. It has been...

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Chapter 28

A Recovery-Oriented Approach for Software Fault Diagnosis in Complex Critical Systems (pages 388-413)

Gabriella Carrozza, Roberto Natella

This paper proposes an approach to software faults diagnosis in complex fault tolerant systems, encompassing the phases of error detection, fault location, and system recovery. Errors are detected in the first phase, exploiting the...

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Chapter 29

Artificial Intelligence Techniques for Unbalanced Datasets in Real World Classification Tasks (pages 414-427)

Marco Vannucci, Valentina Colla, Silvia Cateni, Mirko Sgarbi

In this chapter a survey on the problem of classification tasks in unbalanced datasets is presented. The effect of the imbalance of the distribution of target classes in databases is analyzed with respect to the performance of...

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Chapter 30

Hybrid Meta-Heuristics Based System for Dynamic Scheduling (pages 428-435)

Ana Maria Madureira

The complexity of current computer systems has led the software engineering, distributed systems and management communities to look for inspiration in diverse fields, e.g. robotics, artificial intelligence or biology, to find new...

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Chapter 31

Differential Learning Expert System in Data Management (pages 436-443)

R. Manjunath

Expert systems have been applied to many areas of research to handle problems effectively. Designing and implementing an expert system is a difficult job, and it usually takes experimentation and experience to achieve high...

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Chapter 32

Hybrid Intelligent Diagnosis Approach Based On Neural Pattern Recognition and Fuzzy Decision-Making (pages 444-466)

Amine Chohra, Nadia Kanaoui, Véronique Amarger, Kurosh Madani

Fault diagnosis is a complex and fuzzy cognitive process, and soft computing methods and technologies based on Neural Networks (NN) and Fuzzy Logic (FL), have shown great potential in the development of Decision Support Systems...

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Chapter 33

Machine Learning Approach to Search Query Classification (pages 467-482)

Isak Taksa, Sarah Zelikovitz, Amanda Spink

Search query classification is a necessary step for a number of information retrieval tasks. This chapter presents an approach to non-hierarchical classification of search queries that focuses on two specific areas of machine...

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Chapter 34

Machine Learning in Morphological Segmentation (pages 483-497)

O. Lezoray, G. Lebrun, C. Meurie, C. Charrier, A. Elmotataz, M. Lecluse

The segmentation of microscopic images is a challenging application that can have numerous applications ranging from prognosis to diagnosis. Mathematical morphology is a very well established theory to process images. Segmentation by...

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Chapter 35

Machine Learning Techniques for Network Intrusion Detection (pages 498-521)

Tich Phuoc Tran, Pohsiang Tsai, Tony Jan, Xiangjian He

Most of the currently available network security techniques are not able to cope with the dynamic and increasingly complex nature of cyber attacks on distributed computer systems. Therefore, an automated and adaptive defensive tool...

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Chapter 36

A Machine Learning Based Meta-Scheduler for Multi-Core Processors (pages 522-534)

Jitendra Kumar Rai, Atul Negi, Rajeev Wankar, K. D. Nayak

Sharing resources such as caches and memory buses between the cores of multi-core processors may cause performance bottlenecks for running programs. In this paper, the authors describe a meta-scheduler, which adapts the process...

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Chapter 37

Automatic Semantic Annotation Using Machine Learning (pages 535-578)

Jie Tang, Duo Zhang, Limin Yao, Yi Li

This chapter aims to give a thorough investigation of the techniques for automatic semantic annotation. The Semantic Web provides a common framework that allows data to be shared and reused across applications, enterprises, and...

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Chapter 38

Electricity Load Forecasting Using Machine Learning Techniques (pages 579-597)

Manuel Martín-Merino Acera

Electricity load forecasting has become increasingly important due to the strong impact on the operational efficiency of the power system. However, the accurate load prediction remains a challenging task due to several issues such as...

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Chapter 39

Non-Topical Classification of Query Logs Using Background Knowledge (pages 598-615)

Isak Taksa, Sarah Zelikovitz, Amanda Spink

Background knowledge has been actively investigated as a possible means to improve performance of machine learning algorithms. Research has shown that background knowledge plays an especially critical role in three atypical text...

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Chapter 40

Prediction of Compound-protein Interactions with Machine Learning Methods (pages 616-630)

Yoshihiro Yamanishi, Hisashi Kashima

In silico prediction of compound-protein interactions from heterogeneous biological data is critical in the process of drug development. In this chapter the authors review several supervised machine learning methods to predict...

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Chapter 41

Secure Key Generation for Static Visual Watermarking by Machine Learning in Intelligent Systems and Services (pages 631-646)

Kensuke Naoe, Hideyasu Sasaki, Yoshiyasu Takefuji

The Service-Oriented Architecture (SOA) demands supportive technologies and new requirements for mobile collaboration across multiple platforms. One of its representative solutions is intelligent information security of enterprise...

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Chapter 42

Adaptive Ensemble Multi-Agent Based Intrusion Detection Model (pages 647-659)

Tarek Helmy

The system that monitors the events occurring in a computer system or a network and analyzes the events for sign of intrusions is known as intrusion detection system. The performance of the intrusion detection system can be improved...

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Chapter 43

Class Prediction in Test Sets with Shifted Distributions (pages 660-667)

Óscar Pérez, Manuel Sánchez-Montañés

Machine learning has provided powerful algorithms that automatically generate predictive models from experience. One specific technique is supervised learning , where the machine is trained to predict a desired output for each input...

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Chapter 44

Bankruptcy Prediction by Supervised Machine Learning Techniques: A Comparative Study (pages 668-683)

Chih-Fong Tsai, Yu-Hsin Lu, Yu-Feng Hsu

It is very important for financial institutions which are capable of accurately predicting business failure. In literature, numbers of bankruptcy prediction models have been developed based on statistical and machine learning...

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Chapter 45

Bankruptcy Prediction through Artificial Intelligence (pages 684-693)

Y. Goletsis, C. Papaloukas, Th. Exarhos, C.D. Katsis

Bankruptcy prediction or corporate failure is considered a classic issue in both, academic and business communities. Bankruptcy risk is one of the most important factors (if not the most important one) to be considered when credit...

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Utilization and Application

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Chapter 46

Machine Learning and Data Mining in Bioinformatics (pages 695-703)

George Tzanis, Christos Berberidis, Ioannis Vlahavas

Machine learning is one of the oldest subfields of artificial intelligence and is concerned with the design and development of computational systems that can adapt themselves and learn. The most common machine learning algorithms can...

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Chapter 47

Machine Learning for Biometrics (pages 704-723)

Albert Ali Salah

Biometrics aims at reliable and robust identification of humans from their personal traits, mainly for security and authentication purposes, but also for identifying and tracking the users of smarter applications. Frequently...

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Chapter 48

Pattern Discovery from Biological Data (pages 724-768)

Jesmin Nahar, Kevin S. Tickle, A. B.M. Shawkat Ali

Extracting useful information from structured and unstructured biological data is crucial in the health industry. Some examples include medical practitioner’s need to identify breast cancer patient in the early stage, estimate...

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Chapter 49

Computer-Aided Detection and Diagnosis of Breast Cancer Using Machine Learning, Texture and Shape Features (pages 769-792)

Geraldo Braz Júnior, Leonardo de Oliveira Martins, Aristófanes Corrêa Silva, Anselmo Cardoso de Paiva

Breast cancer is a malignant (cancer) tumor that starts from cells of the breast, being the major cause of deaths by cancer in the female population. There has been tremendous interest in the use of image processing and analysis...

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Chapter 50

Ensemble of Neural Networks for Automated Cell Phenotype Image Classification (pages 793-816)

Loris Nanni, Alessandra Lumini

Subcellular location is related to the knowledge of the spatial distribution of a protein within the cell. The knowledge of the location of all proteins is crucial for several applications ranging from early diagnosis of a disease to...

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Chapter 51

Image Processing and Machine Learning Techniques for the Segmentation of cDNA Microarray Images (pages 817-829)

Nikolaos Giannakeas, Dimitrios I. Fotiadis

Microarray technology allows the comprehensive measurement of the expression level of many genes simultaneously on a common substrate. Typical applications of microarrays include the quantification of expression profiles of a system...

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Chapter 52

Machine Learning for Automated Polyp Detection in Computed Tomography Colonography (pages 830-850)

Abhilash Alexander Miranda, Olivier Caelen, Gianluca Bontempi

This chapter presents a comprehensive scheme for automated detection of colorectal polyps in computed tomography colonography (CTC) with particular emphasis on robust learning algorithms that differentiate polyps from non-polyp...

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Chapter 53

Machine Learning for Brain Image Segmentation (pages 851-874)

Jonathan Morra, Zhuowen Tu, Arthur Toga, Paul Thompson

In this chapter, the authors review a variety of algorithms developed by different groups for automatically segmenting structures in medical images, such as brain MRI scans. Some of the simpler methods, based on active contours...

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Chapter 54

Machine Learning for Clinical Data Processing (pages 875-897)

Guo-Zheng Li

This chapter introduces great challenges and the novel machine learning techniques employed in clinical data processing. It argues that the novel machine learning techniques including support vector machines, ensemble learning...

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Chapter 55

A Simulation of Temporally Variant Agent Interaction via Passive Inquiry (pages 898-912)

Adam J. Conover

This chapter presents a description of ongoing experimental research into the emergent properties of multi-agent communication in “temporally asynchronous” environments. Many traditional agent and swarm simulation environments divide...

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Chapter 56

A Simulation of Temporally Variant Agent Interaction via Belief Promulgation (pages 913-927)

Adam J. Conover

This chapter concludes a two part series which examines the emergent properties of multi-agent communication in “temporally asynchronous” environments. Many traditional agent and swarm simulation environments divide time into...

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Chapter 57

Application of Uncertain Variables to Knowledge-Based Resource Distribution (pages 928-950)

Donat Orski

The chapter concerns a class of systems composed of operations performed with the use of resources allocated to them. In such operation systems, each operation is characterized by its execution time depending on the amount of a...

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Chapter 58

Applying Commonsense Reasoning to Place Identification (pages 951-968)

Marco Mamei

Recent mobile computing applications try to automatically identify the places visited by the user from a log of GPS readings. Such applications reverse geocode the GPS data to discover the actual places (shops, restaurants, etc.)...

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Chapter 59

Machine Learning Enhancing Adaptivity of Multimodal Mobile Systems (pages 969-985)

Floriana Esposito, Teresa M.A. Basile, Nicola Di Mauro, Stefano Ferilli

One of the most important features of a mobile device concerns its flexibility and capability to adapt the functionality it provides to the users. However, the main problems of the systems present in literature are their incapability...

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Chapter 60

Visual Semantic Analysis to Support Semi-Automatic Modeling of Semantic Service Descriptions (pages 986-1033)

Nadeem Bhatti, Dieter W. Fellner

The service-oriented architecture has become one of the most popular approaches for distributed business applications. A new trend service ecosystem is merging, where service providers can augment their core services by using...

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Chapter 61

Learning Algorithms for RBF Functions and Subspace Based Functions (pages 1034-1065)

Lei Xu

Among extensive studies on radial basis function (RBF), one stream consists of those on normalized RBF (NRBF) and extensions. Within a probability theoretic framework, NRBF networks relates to nonparametric studies for decades in the...

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Chapter 62

Annotating Images by Mining Image Search (pages 1066-1089)

Xin-Jing Wang, Lei Zhang, Xirong Li, Wei-Ying Ma

Although it has been studied for years by computer vision and machine learning communities, image annotation is still far from practical. In this chapter, the authors propose a novel attempt of modeless image annotation, which...

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Chapter 63

Machine Learning for Visual Navigation of Unmanned Ground Vehicles (pages 1090-1107)

Artem A. Lenskiy, Jong-Soo Lee

The use of visual information for the navigation of unmanned ground vehicles in a cross-country environment recently received great attention. However, until now, the use of textural information has been somewhat less effective than...

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Chapter 64

Empirical Evaluation of Ensemble Learning for Credit Scoring (pages 1108-1127)

Gang Wang, Jin-xing Hao, Jian Ma, Li-hua Huang

Credit scoring is an important finance activity. Both statistical techniques and Artificial Intelligence (AI) techniques have been explored for this topic. But different techniques have different advantages and disadvantages on...

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Chapter 65

A Case Study on Scaffolding Adaptive Feedback within Virtual Learning Environments (pages 1128-1144)

Mehdi Najjar

Despite a growing development of virtual laboratories which use the advantages of multimedia and the Internet for distance education, learning by means of such tutorial tools would be more effective if they were specifically tailored...

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Organizational and Social Implications

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Chapter 66

Conservation of Information (COI): Geospatial and Operational Developments in E-Health and Telemedicine for Virtual and Rural Communities (pages 1146-1167)

Max E. Stachura, Elena V. Astapova, Hui-Lien Tung, Donald A. Sofge, James Grayson, Margo Bergman, Joseph Wood

The authors review telemedicine and e-health from an organizational perspective. To evaluate their effectiveness, they review organizational and system theory along with field and laboratory results. Theory of the conservation of...

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Chapter 67

Computational Intelligence for Functional Testing (pages 1168-1191)

C. Peng Lam

Software testing is primarily a technique for achieving some degree of software quality and to gain consumer confidence. It accounts for 50% -75% of development cost. Test case design supports effective testing but is still a human...

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Chapter 68

An Immune Inspired Algorithm for Learning Strategies in a Pursuit-Evasion Game (pages 1192-1214)

Malgorzata Lucinska, Slawomir T. Wierzchon

Multi-agent systems (MAS), consist of a number of autonomous agents, which interact with one-another. To make such interactions successful, they will require the ability to cooperate, coordinate, and negotiate with each other. From a...

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Chapter 69

Artificial Intelligence in Software Engineering: Current Developments and Future Prospects (pages 1215-1236)

Farid Meziane, Sunil Vadera

Artificial intelligences techniques such as knowledge based systems, neural networks, fuzzy logic and data mining have been advocated by many researchers and developers as the way to improve many of the software development...

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Chapter 70

FOL Learning for Knowledge Discovery in Documents (pages 1237-1262)

Stefano Ferilli, Floriana Esposito, Marenglen Biba, Teresa M.A. Basile, Nicola Di Mauro

This chapter proposes the application of machine learning techniques, based on first-order logic as a representation language, to the real-world application domain of document processing. First, the tasks and problems involved in...

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Chapter 71

Computer-Based Learning Environments with Emotional Agents (pages 1263-1291)

Dorel Gorga, Daniel K. Schneider

The purpose of this contribution is to discuss conceptual issues and challenges related to the integration of emotional agents in the design of computer-based learning environments and to propose a framework for the discussion of...

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Chapter 72

Emotional Memory and Adaptive Personalities (pages 1292-1313)

Anthony G. Francis Jr., Manish Mehta, Ashwin Ram

Believable agents designed for long-term interaction with human users need to adapt to them in a way which appears emotionally plausible while maintaining a consistent personality. For short-term interactions in restricted...

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Chapter 73

Hybrid Emotionally Aware Mediated Multiagency (pages 1314-1329)

Giovanni Vincenti, James Braman

Emotions influence our everyday lives, guiding and misguiding us. They lead us to happiness and love, but also to irrational acts. Artificial intelligence aims at constructing agents that can emulate thinking processes, but...

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Chapter 74

Automatic Detection of Emotion in Music: Interaction with Emotionally Sensitive Machines (pages 1330-1354)

Cyril Laurier, Perfecto Herrera

Creating emotionally sensitive machines will significantly enhance the interaction between humans and machines. In this chapter we focus on enabling this ability for music. Music is extremely powerful to induce emotions. If machines...

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Chapter 75

Improving Automated Planning with Machine Learning (pages 1355-1373)

Susana Fernández Arregui, Sergio Jiménez Celorrio, Tomás de la Rosa Turbides

This chapter reports the last machine learning techniques for the assistance of automated planning. Recent discoveries in automated planning have opened the scope of planners, from toy problems to real-world applications, making new...

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Chapter 76

Diagnostic Support Systems and Computational Intelligence: Differential Diagnosis of Hepatic Lesions from Computed Tomography Images (pages 1374-1388)

Stavroula Mougiakakou, Ioannis Valavanis, Alexandra Nikita, Konstantina S. Nikita

Recent advances in computer science provide the intelligent computation tools needed to design and develop Diagnostic Support Systems (DSSs) that promise to increase the efficiency of physicians during their clinical practice. This...

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Chapter 77

Computer Aided Knowledge Discovery in Biomedicine (pages 1389-1403)

Vanathi Gopalakrishnan

This chapter provides a perspective on 3 important collaborative areas in systems biology research. These areas represent biological problems of clinical significance. The first area deals with macromolecular crystallization, which...

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Chapter 78

Computerised Decision Support for Women’s Health Informatics (pages 1404-1416)

David Parry

Decision analysis techniques attempt to utilize mathematical data about outcomes and preferences to help people make optimal decisions. The increasing uses of computerized records and powerful computers have made these techniques...

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Chapter 79

Translation of Biomedical Terms by Inferring Rewriting Rules (pages 1417-1433)

Vincent Claveau

This chapter presents a simple yet efficient approach to translate automatically unknown biomedical terms from one language into another. This approach relies on a machine learning process able to infer rewriting rules from examples...

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Chapter 80

Machine Learning in Personalized Anemia Treatment (pages 1434-1444)

Adam E. Gaweda

This chapter presents application of reinforcement learning to drug dosing personalization in treatment of chronic conditions. Reinforcement learning is a machine learning paradigm that mimics the trialand- error skill acquisition...

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Chapter 81

An Intelligent Algorithm for Home Sleep Apnoea Test Device (pages 1445-1459)

Ahsan H. Khandoker

In this chapter authors try to develop a system for Sleep apnea with the help of machine learning algorithms using ECG signals. The application of an intelligent machine learning technique (Support Vector Machines, SVM) to...

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Chapter 82

Application of Machine Leaning in Drug Discovery and Development (pages 1460-1482)

Shuxing Zhang

Machine learning techniques have been widely used in drug discovery and development, particularly in the areas of cheminformatics, bioinformatics and other types of pharmaceutical research. It has been demonstrated they are suitable...

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Chapter 83

Learning and Prediction of Complex Molecular Structure-Property Relationships: Issues and Strategies for Modeling Intestinal Absorption for Drug Discovery (pages 1482-1498)

Rahul Singh

The problem of modeling and predicting complex structure-property relationships, such as the absorption, distribution, metabolism, and excretion of putative drug molecules is a fundamental one in contemporary drug discovery. An...

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Chapter 84

Artificial Intelligence and Rubble-Mound Breakwater Stability (pages 1499-1506)

Gregorio Iglesias Rodriguez, Alberte Castro Ponte, Rodrigo Carballo Sanchez, Miguel Ángel Losada Rodriguez

Breakwaters are coastal structures constructed to shelter a harbour basin from waves. There are two main types: rubble-mound breakwaters, consisting of various layers of stones or concrete pieces of different sizes (weights), making...

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Chapter 85

Decision Support System for Greenhouse Tomato Yield Prediction using Artificial Intelligence Techniques (pages 1507-1523)

F. Zhang, D. D. Iliescu, E. L. Hines, M. S. Leeson, S. R. Adams

This chapter introduces a decision support system which is capable of predicting the weekly yields of tomatoes in a greenhouse. The development of this system involves a set of Artificial Intelligence based techniques, namely...

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Managerial Impact

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Chapter 86

Introducing AI and IA into a Non Computer Science Graduate Programme (pages 1525-1537)

Ioanna Stamatopoulou, Maria Fasli, Petros Kefalas

As part of designing a new Master’s programme entitled Technology, Innovation and Entrepreneurship there was an apparent need to include a unit involving the use of innovative technologies for the development of innovative products...

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Chapter 87

Distributed Intelligence for Constructing Economic Models (pages 1538-1550)

Ting Yu

This paper presents an integrated and distributed intelligent system being capable of automatically estimating and updating large-size economic models. The input-output model of economics uses a matrix representation of a nation’s...

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Chapter 88

A Computational Intelligence Approach to Supply Chain Demand Forecasting (pages 1551-1565)

Nicholas Ampazis

Estimating customer demand in a multi-level supply chain structure is crucial for companies seeking to maintain their competitive advantage within an uncertain business environment. This work explores the potential of computational...

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Chapter 89

Artificial Intelligence Applied to Natural Resources Management (pages 1566-1582)

Diana F. Adamatti, Marilton S. de Aguiar

There are three computational challenges in natural resources management: data management and communication; data analysis; and optimization and control. The authors believe these three challenges can be dealt with Artificial...

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Chapter 90

Balance Modelling and Implementation of Flow Balance for Application in Air Traffic Management (pages 1583-1600)

Bueno Borges de Souza, Li Weigang, Antonio Marcio Ferreira Crespo, Victor Rafael Rezende Celestino

This work describes a decision making support system with Graph Theory and Artificial Intelligence methodologies applied to the Brazilian Air Traffic Flow Management. It consists of a flow management model based on graphs with...

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Chapter 91

Computational Intelligence for Information Technology Project Management (pages 1601-1624)

Robert J. Hammell, Julie Hoksbergen, James Wood, Mark Christensen

With the growing complexity of information technology (IT) projects, the management of these projects is proving to be a daunting task. The magnitude of this problem is underscored by the assertion that approximately 70% of IT...

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Chapter 92

Cost-Sensitive Learning in Medicine (pages 1625-1641)

Alberto Freitas, Pavel Brazdil, Altamiro Costa-Pereira

This chapter introduces cost-sensitive learning and its importance in medicine. Health managers and clinicians often need models that try to minimize several types of costs associated with healthcare, including attribute costs (e.g....

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Chapter 93

Data Warehousing and Decision Support in Mobile Wireless Patient Monitoring (pages 1642-1651)

Barin N. Nag, Mark Siegal

The recent advances in wireless communication technologies have made possible the development of wireless systems for monitoring the health and disease status of patients, in both in-patient hospital settings and outside. The volume...

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Chapter 94

Forecasting Supply Chain Demand Using Machine Learning Algorithms (pages 1652-1686)

Réal Carbonneau, Rustam Vahidov, Kevin Laframboise

Managing supply chains in today’s complex, dynamic, and uncertain environment is one of the key challenges affecting the success of the businesses. One of the crucial determinants of effective supply chain management is the ability...

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Chapter 95

Machine Learning and Financial Investing (pages 1687-1697)

Jie Du, Roy Rada

This chapter presents the case for knowledge-based machine learning in financial investing. Machine learning here, while it will exploit knowledge, will also rely heavily on the evolutionary computation paradigm of learning, namely...

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Critical Issues

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Chapter 96

Problems for Structure Learning Aggregation and Computational Complexity (pages 1699-1720)

Frank Wimberly, David Danks, Clark Glymour, Tianjiao Chu

Machine learning methods to find graphical models of genetic regulatory networks from cDNA microarray data have become increasingly popular in recent years. We provide three reasons to question the reliability of such methods: (1) a...

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Chapter 97

Granular Computing and Human-Centricity in Computational Intelligence (pages 1721-1735)

Witold Pedrycz

Information granules and ensuing Granular Computing offer interesting opportunities to endow processing with an important facet of human-centricity. This facet implies that the underlying processing supports non-numeric data...

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Chapter 98

Walking the Information Overload Tightrope (pages 1736-1752)

A. Pablo Iannone

This chapter asks: What is information overload? At what levels of existence does it occur? Are there any features common to information overload at all these levels? What are information overload’s types? What are information...

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Chapter 99

Moral Emotions for Autonomous Agents (pages 1753-1766)

Antoni Gomila, Alberto Amengual

In this chapter we raise some of the moral issues involved in the current development of robotic autonomous agents. Starting from the connection between autonomy and responsibility, we distinguish two sorts of problems: those having...

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Chapter 100

Artificial Moral Agency in Technoethics (pages 1767-1783)

John P. Sullins

This chapter will argue that artificial agents created or synthesized by technologies such as artificial life (ALife), artificial intelligence (AI), and in robotics present unique challenges to the traditional notion of moral agency...

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Chapter 101

Emotions, Diffusive Emotional Control and the Motivational Problem for Autonomous Cognitive Systems (pages 1784-1797)

C. Gros

All self-active living beings need to solve the motivational problem—the question of what to do at any moment of their life. For humans and non-human animals at least two distinct layers of motivational drives are known, the primary...

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Chapter 102

Embodying Cognition: A Morphological Perspective (pages 1798-1818)

David Casacuberta, Saray Ayala, Jordi Vallverdú

After several decades of success in different areas and numerous effective applications, algorithmic Artificial Intelligence has revealed its limitations. If in our quest for artificial intelligence we want to understand natural...

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Chapter 103

A Cognitive Computational Knowledge Representation Theory (pages 1819-1838)

Mehdi Najjar, André Mayers

Encouraging results of last years in the field of knowledge representation within virtual learning environments confirms that artificial intelligence research in this topic find it very beneficial to integrate the knowledge...

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Chapter 104

Noble Ape’s Cognitive Simulation: From Agar to Dreaming and Beyond (pages 1839-1855)

Thomas S. Barbalet

Inspired by observing bacterial growth in agar and by the transfer of information through simple agar simulations, the cognitive simulation of Noble Ape (originally developed in 1996) has defined itself as both a philosophical...

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Chapter 105

Ethology-Based Approximate Adaptive Learning: A Near Set Approach (pages 1856-1878)

James F. Peters, Shabnam Shahfar

The problem considered in this chapter is how to use the observed behavior of organisms as a basis for machine learning. The proposed approach for machine learning combines near sets and ethology. It leads to novel forms of...

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Emerging Trends

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Chapter 106

Learning with Partial Supervision (pages 1880-1888)

Abdelhamid Bouchachia

Recently the field of machine learning, pattern recognition, and data mining has witnessed a new research stream that is learning with partial supervisio n -LPS- (known also as semi-supervised learning ). This learning scheme is...

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Chapter 107

Brain-Like Processing and Classification of Chemical Data: An Approach Inspired by the Sense of Smell (pages 1889-1902)

Michael Schmuker, Gisbert Schneider

The purpose of the olfactory system is to encode and classify odorants. Hence, its circuits have likely evolved to cope with this task in an efficient, quasi-optimal manner. In this chapter the authors present a three-step approach...

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Chapter 108

Modern Approaches to Software Engineering in the Compositional Era (pages 1903-1923)

Ali Dogru, Pinar Senkul, Ozgur Kaya

The amazing evolution fuelled by the introduction of the computational element has already changed our lives and continues to do so. Initially, the fast advancement in hardware partially enabled an appreciation for software potency....

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Chapter 109

Pattern Discovery as Event Association (pages 1924-1932)

Andrew K.C. Wong, Yang Wang, Gary C.L. Li

A basic task of machine learning and data mining is to automatically uncover patterns that reflect regularities in a data set. When dealing with a large database, especially when domain knowledge is not available or very weak, this...

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Chapter 110

A Survey of Optimized Learning Pathway Planning and Assessment Paper Generation with Swarm Intelligence (pages 1933-1950)

Lung-Hsiang Wong, Chee-Kit Looi

One major direction in research on technology-enabled learning systems revolves round the notion of generating optimal learning pathways. Two examples of the application areas that could be presented as search and optimization...

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Chapter 111

A Next Generation Technology Victim Location and Low Level Assessment Framework for Occupational Disasters Caused by Natural Hazards (pages 1951-1960)

Nik Bessis, Eleana Asimakopoulou, Peter Norrington, Suresh Thomas, Ravi Varaganti

Much work is underway within the broad next generation technologies community on issues associated with the development of services to support interdisciplinary domains. Disaster reduction and emergency management are domains in...

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Chapter 112

Facial Expression Analysis by Machine Learning (pages 1961-1980)

Siu-Yeung Cho, Teik-Toe Teoh, Yok-Yen Nguwi

Facial expression recognition is a challenging task. A facial expression is formed by contracting or relaxing different facial muscles on human face that results in temporally deformed facial features like wide-open mouth, raising...

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Chapter 113

Discovering Semantics from Visual Information (pages 1981-2009)

Zhiyong Wang, Dagan Feng

Visual information has been immensely used in various domains such as web, education, health, and digital libraries, due to the advancements of computing technologies. Meanwhile, users realize that it has been more and more difficult...

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Chapter 114

From Biomedical Image Analysis to Biomedical Image Understanding Using Machine Learning (pages 2010-2034)

Eduardo Romero, Fabio González

This chapter introduces the reader into the main topics covered by the book: biomedical images, biomedical image analysis and machine learning. The general concepts of each topic are presented and the most representative techniques...

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Chapter 115

The Application of Machine Learning Technique for Malaria Diagnosis (pages 2035-2043)

C. Ugwu, N. L Onyejegbu, I. C Obagbuwa

Healthcare delivery in African nations has long been a worldwide issue, which is why the United Nations and World Health Organization seek for ways to alleviate this problem and thereby reduce the number of lives that are lost every...

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Chapter 116

Application of Machine Learning Techniques for Railway Health Monitoring (pages 2044-2067)

G.M. Shafiullah, Adam Thompson, Peter J. Wolfs, A.B.M. Shawkat Ali

Emerging wireless sensor networking (WSN) and modern machine learning techniques have encouraged interest in the development of vehicle health monitoring (VHM) systems that ensure secure and reliable operation of the rail vehicle....

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Chapter 117

Explorative Data Analysis of In-Vitro Neuronal Network Behavior Based on an Unsupervised Learning Approach (pages 2068-2080)

A. Maffezzoli, E. Wanke

In the present chapter authors want to expose new insights in the field of Computational Neuroscience at regard to the study of neuronal networks grown in vitro. Such kind of analyses can exploit the availability of a huge amount of...

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Chapter 118

Modeling the Ecological Footprint of Nations via Evolutionary Computation and Machine Learning Models (pages 2081-2100)

Mohamed M. Mostafa

The per capita Ecological Footprint (EF) is one of the most-widely recognized measures of environmental sustainability. It seeks to quantify the Earth’s biological capacity required to support human activity. This study uses gene...

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Chapter 119

Adaptive Interaction for Mass Customisation (pages 2101-2116)

Gulden Uchyigit

The popularisation of mass customization and the need for integration of the user needs into the design, production and marketing phases has called for more innovative methods to be introduced into this area. At present the...

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Chapter 120

Dependency Parsing: Recent Advances (pages 2117-2124)

Ruket Çakici

Annotated data have recently become more important, and thus more abundant, in computational linguistics . They are used as training material for machine learning systems for a wide variety of applications from Parsing to Machine...

Machine Learning: Concepts, Methodologies, Tools and Applications

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