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Algorithms for Solving Financial Portfolio Design Problems: Emerging Research and Opportunities
In the current scope of economics, the management of client portfolios has become a considerable problem within financial institutions due to the amount of risk that goes into assigning assets. Various algorithmic models exist for solving these portfolio challenges; however, considerable research is lacking that further explains these design problems and provides applicable solutions to these imperative issues. Algorithms for Solving Financial Portfolio Design Problems: Emerging Research and Opportunities is a pivotal reference source that provides vital research on the application of various programming models within the financial engineering field. While highlighting topics such as landscape analysis, breaking symmetries, and linear programming, this publication analyzes the quadratic constraints of current portfolios and provides algorithmic solutions to maximizing the full value of these financial sets. This book is ideally designed for financial strategists, engineers, programmers, mathematicians, banking professionals, researchers, academicians, and students seeking current research on recent mathematical advances within financial engineering.
Economics, Business, and Islamic Finance in ASEAN Economics Community
The economic integration of Southeast Asia or ASEAN Economic Community (AEC) offers enormous opportunities for its members to develop and collectively collaborate with other economies. Combining the culture of the region with global business in an expanding digital atmosphere, however, has caused numerous challenges on an international scale. Due to the importance of this economic player in Asia, research on key topics including Islamic economics, Islamic finance, technology, and cultural issues in doing business are essential to understand the ASEAN competitive landscape and its relations with other countries. Economics, Business, and Islamic Finance in ASEAN Economics Community is a pivota...
Growth and Emerging Prospects of International Islamic Banking
As an ever-growing international business, Islamic banking has changed the face of economics in recent years. As more and more industries embrace Islamic principles, the industry will unquestionably influence modern economic practices and techniques across the globe. Growth and Emerging Prospects of International Islamic Banking is a collection of innovative research on the methods and applications of Islamic banking interests on a global economic scale. While highlighting topics including asset diversification, profit sharing, and financial reporting, this book is ideally designed for bankers, banking analysts, international business managers, financiers, industry professionals, economists, government officials, academicians, students, and researchers seeking current research on Islamic banking perspectives and approaches to finances.
Innovation in Information Systems and Technologies to Support Learning Research
This book provides glimpses into contemporary research in information systems & technology, learning, artificial intelligence (AI), machine learning, and security and how it applies to the real world, but the ideas presented also span the domains of telehealth, computer vision, the role and use of mobile devices, brain–computer interfaces, virtual reality, language and image processing and big data analytics and applications. Great research arises from asking pertinent research questions. This book reveals some of the authors’ “beautiful questions” and how they develop the subsequent “what if” and “how” questions, offering readers food for thought and whetting their appetite for further research by the same authors.
High-Utility Pattern Mining
This book presents an overview of techniques for discovering high-utility patterns (patterns with a high importance) in data. It introduces the main types of high-utility patterns, as well as the theory and core algorithms for high-utility pattern mining, and describes recent advances, applications, open-source software, and research opportunities. It also discusses several types of discrete data, including customer transaction data and sequential data. The book consists of twelve chapters, seven of which are surveys presenting the main subfields of high-utility pattern mining, including itemset mining, sequential pattern mining, big data pattern mining, metaheuristic-based approaches, privacy-preserving pattern mining, and pattern visualization. The remaining five chapters describe key techniques and applications, such as discovering concise representations and regular patterns.
Advances in Knowledge Discovery and Management
During the last decade, the French-speaking scientific community developed a very strong research activity in the field of Knowledge Discovery and Management (KDM or EGC for “Extraction et Gestion des Connaissances” in French), which is concerned with, among others, Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and SemanticWeb. The recent and novel research contributions collected in this book are extended and reworked versions of a selection of the best papers that were originally presented in French at the EGC 2009 Conference held in Strasbourg, France on January 2009. The volume is organized in four parts. Part I includes five papers concerned by various aspects of supervised learning or information retrieval. Part II presents five papers concerned with unsupervised learning issues. Part III includes two papers on data streaming and two on security while in Part IV the last four papers are concerned with ontologies and semantic.
Periodic Pattern Mining
This book provides an introduction to the field of periodic pattern mining, reviews state-of-the-art techniques, discusses recent advances, and reviews open-source software. Periodic pattern mining is a popular and emerging research area in the field of data mining. It involves discovering all regularly occurring patterns in temporal databases. One of the major applications of periodic pattern mining is the analysis of customer transaction databases to discover sets of items that have been regularly purchased by customers. Discovering such patterns has several implications for understanding the behavior of customers. Since the first work on periodic pattern mining, numerous studies have been...
Cloud Data Management
In practice, the design and architecture of a cloud varies among cloud providers. We present a generic evaluation framework for the performance, availability and reliability characteristics of various cloud platforms. We describe a generic benchmark architecture for cloud databases, specifically NoSQL database as a service. It measures the performance of replication delay and monetary cost. Service Level Agreements (SLA) represent the contract which captures the agreed upon guarantees between a service provider and its customers. The specifications of existing service level agreements (SLA) for cloud services are not designed to flexibly handle even relatively straightforward performance and...
Advances in Knowledge Discovery and Management
This book is a collection of high scientific novel contributions addressing several of these challenges. These articles are extended versions of a selection of the best papers that were initially presented at the French-speaking conferences EGC’2019held in Metz (France, January 21-25, 2019). These extended versions have been accepted after an additional peer-review process among papers already accepted in long format at the conference. Concerning the conference, the long and short papers selection were also the result of a double blind peer review process among the hundreds of papers initially submitted to each edition of the conference (acceptance rate for long papers is about 25%.
