Tharam S. Dillon – författare

Mining of Data with Complex Structures:- Clarifies the type and nature of data with complex structure including sequences, trees and graphs- Provides a detailed background of the state-of-the-art of sequence mining, tree mining and graph mining.- Defines the essential aspects of the tree mining problem: subtree types, support definitions, constraints.- Outlines the implementation issues one needs to consider when developing tree mining algorithms (enumeration strategies, data structures, etc.)- Details the Tree Model Guided (TMG) approach for tree mining and provides the mathematical model for the worst case estimate of complexity of mining ordered induced and embedded subtrees.-  Explains the mechanism of the TMG framework for mining ordered/unordered induced/embedded and distance-constrained embedded subtrees.-  Provides a detailed comparison of the different tree mining approaches highlighting the characteristics and benefits of each approach.-  Overviews the implications and potential applications of tree mining in general knowledge management related tasks, and uses Web, health and bioinformatics related applications as case studies.-  Details the extension of the TMG framework for sequence mining- Provides an overview of the future research direction with respect to technical extensions and application areasThe primary audience is 3rd year, 4th year undergraduate students, Masters and PhD students and academics. The book can be used for both teaching and research. The secondary audiences are practitioners in industry, business, commerce, government and consortiums, alliances and partnerships to learn how to introduce and efficiently make use of the techniques for mining of data with complex structures into their applications. The scope of the book is both theoretical and practical and as such it will reach a broad market both within academia and industry.In addition, its subject matter is a rapidly emerging field that is critical for efficient analysis of knowledge stored in various domains.

Mining of Data with Complex Structures:- Clarifies the type and nature of data with complex structure including sequences, trees and graphs- Provides a detailed background of the state-of-the-art of sequence mining, tree mining and graph mining.- Defines the essential aspects of the tree mining problem: subtree types, support definitions, constraints.- Outlines the implementation issues one needs to consider when developing tree mining algorithms (enumeration strategies, data structures, etc.)- Details the Tree Model Guided (TMG) approach for tree mining and provides the mathematical model for the worst case estimate of complexity of mining ordered induced and embedded subtrees.-  Explains the mechanism of the TMG framework for mining ordered/unordered induced/embedded and distance-constrained embedded subtrees.-  Provides a detailed comparison of the different tree mining approaches highlighting the characteristics and benefits of each approach.-  Overviews the implications and potential applications of tree mining in general knowledge management related tasks, and uses Web, health and bioinformatics related applications as case studies.-  Details the extension of the TMG framework for sequence mining- Provides an overview of the future research direction with respect to technical extensions and application areasThe primary audience is 3rd year, 4th year undergraduate students, Masters and PhD students and academics. The book can be used for both teaching and research. The secondary audiences are practitioners in industry, business, commerce, government and consortiums, alliances and partnerships to learn how to introduce and efficiently make use of the techniques for mining of data with complex structures into their applications. The scope of the book is both theoretical and practical and as such it will reach a broad market both within academia and industry.In addition, its subject matter is a rapidly emerging field that is critical for efficient analysis of knowledge stored in various domains.

Applying computational intelligence for product design is a fast-growing and promising research area in computer sciences and industrial engineering. However, there is currently a lack of books, which discuss this research area. This book discusses a wide range of computational intelligence techniques for implementation on product design. It covers common issues on product design from identification of customer requirements in product design, determination of importance of customer requirements, determination of optimal design attributes, relating design attributes and customer satisfaction, integration of marketing aspects into product design, affective product design, to quality control of new products. Approaches for refinement of computational intelligence are discussed, in order to address different issues on product design. Cases studies of product design in terms of development of real-world new products are included, in order to illustrate the design procedures, as well as the effectiveness of the computational intelligence based approaches to product design. This book covers the state-of-art of computational intelligence methods for product design, which provides a clear picture to post-graduate students in industrial engineering and computer science. It is particularly suitable for researchers and professionals working on computational intelligence for product design. It provides concepts, techniques and methodologies, for product designers in applying computational intelligence to deal with product design.

Risk and reward are always foremost in the determination of investment decisions and business transactions. Advances in the area of Information Communication Technologies (ICT) have enabled the development of new business paradigms. Such paradigms involve transactions taking place between loosely connected parties, often totally or partially unknown to one another. One important concept required to ensure such transactions are successful is transactional risk. The importance of doing this has been demonstrated in recent financial crisis. This book is unique in simultaneously taking into account the likelihood of an event occurring and its financial impact and provides an integrated discussion of the process of transactional risk identification, assessment, evaluation, management and recording in these emerging domains. It provides a detailed and clear exposition of the importance of transactional risk before detailing for its assessment and evaluation.  The scope of the book is theoretical and practical and as such it will have a broad market both within academia and industry. Specifically this book should be of primary interest to researchers, graduate students and practitioners in the area of developing business intelligence techniques and their application in various real world applications.

Applying computational intelligence for product design is a fast-growing and promising research area in computer sciences and industrial engineering. However, there is currently a lack of books, which discuss this research area. This book discusses a wide range of computational intelligence techniques for implementation on product design. It covers common issues on product design from identification of customer requirements in product design, determination of importance of customer requirements, determination of optimal design attributes, relating design attributes and customer satisfaction, integration of marketing aspects into product design, affective product design, to quality control of new products. Approaches for refinement of computational intelligence are discussed, in order to address different issues on product design. Cases studies of product design in terms of development of real-world new products are included, in order to illustrate the design procedures, as well as the effectiveness of the computational intelligence based approaches to product design. This book covers the state-of-art of computational intelligence methods for product design, which provides a clear picture to post-graduate students in industrial engineering and computer science. It is particularly suitable for researchers and professionals working on computational intelligence for product design. It provides concepts, techniques and methodologies, for product designers in applying computational intelligence to deal with product design.

Risk and reward are always foremost in the determination of investment decisions and business transactions. Advances in the area of Information Communication Technologies (ICT) have enabled the development of new business paradigms. Such paradigms involve transactions taking place between loosely connected parties, often totally or partially unknown to one another. One important concept required to ensure such transactions are successful is transactional risk. The importance of doing this has been demonstrated in recent financial crisis. This book is unique in simultaneously taking into account the likelihood of an event occurring and its financial impact and provides an integrated discussion of the process of transactional risk identification, assessment, evaluation, management and recording in these emerging domains. It provides a detailed and clear exposition of the importance of transactional risk before detailing for its assessment and evaluation.  The scope of the book is theoretical and practical and as such it will have a broad market both within academia and industry. Specifically this book should be of primary interest to researchers, graduate students and practitioners in the area of developing business intelligence techniques and their application in various real world applications.

Recent years have seen the development of two significant trends namely: the adoption of some Traditional Chinese Medicine Practices into mainstream Allopathic Western Medicine and the advent of the internet and broad band networks leading to an increased interest in the use of Telemedicine to deliver medical services.In this book, we see the convergence of these two trends leading to a semantically-based TCM Telemedicine system that utilizes an ontology to provide sharable knowledge in the TCM realm to achieve this.The underpinning research required the development of a three-layer architecture and an Ontology of the TCM knowledge.As TCM knowledge like all medical knowledge is not frozen in time it was important to develop an approach that would allow evolution of the Ontology when new evidence became available.In order for the system to be practically grounded it was important to work with an industry partner PuraPharm Group/HerbMiners Informatics Limited. This partnership was initiated through Professor Allan Wong and the Chairman of PuraPharm Group Mr. Abraham Chan. This led to the system being utilized in more than 20 Mobile Clinics in Hong Kong and 300 Hospitals in China.In order for these different deployments of the system to be coherent with the main core Ontology, it was necessary for us to develop an Ontology Driven Software System Generation approach.