Decision Tree And Ensemble Learning Based On Ant Colony Optimization

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Decision Tree and Ensemble Learning Based on Ant Colony Optimization

Author : Jan Kozak
Publisher : Springer
ISBN 13 : 3319937529
Total Pages : 159 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Decision Tree and Ensemble Learning Based on Ant Colony Optimization by : Jan Kozak

Download or read book Decision Tree and Ensemble Learning Based on Ant Colony Optimization written by Jan Kozak and published by Springer. This book was released on 2018-06-20 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book not only discusses the important topics in the area of machine learning and combinatorial optimization, it also combines them into one. This was decisive for choosing the material to be included in the book and determining its order of presentation. Decision trees are a popular method of classification as well as of knowledge representation. At the same time, they are easy to implement as the building blocks of an ensemble of classifiers. Admittedly, however, the task of constructing a near-optimal decision tree is a very complex process. The good results typically achieved by the ant colony optimization algorithms when dealing with combinatorial optimization problems suggest the possibility of also using that approach for effectively constructing decision trees. The underlying rationale is that both problem classes can be presented as graphs. This fact leads to option of considering a larger spectrum of solutions than those based on the heuristic. Moreover, ant colony optimization algorithms can be used to advantage when building ensembles of classifiers. This book is a combination of a research monograph and a textbook. It can be used in graduate courses, but is also of interest to researchers, both specialists in machine learning and those applying machine learning methods to cope with problems from any field of R&D.

Decision Tree and Ensemble Learning Based on Ant Colony Optimization

Author : Jan Kozak
Publisher :
ISBN 13 : 9783319937533
Total Pages : 159 pages
Book Rating : 4.9/5 (375 download)

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Book Synopsis Decision Tree and Ensemble Learning Based on Ant Colony Optimization by : Jan Kozak

Download or read book Decision Tree and Ensemble Learning Based on Ant Colony Optimization written by Jan Kozak and published by . This book was released on 2019 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book not only discusses the important topics in the area of machine learning and combinatorial optimization, it also combines them into one. This was decisive for choosing the material to be included in the book and determining its order of presentation. Decision trees are a popular method of classification as well as of knowledge representation. At the same time, they are easy to implement as the building blocks of an ensemble of classifiers. Admittedly, however, the task of constructing a near-optimal decision tree is a very complex process. The good results typically achieved by the ant colony optimization algorithms when dealing with combinatorial optimization problems suggest the possibility of also using that approach for effectively constructing decision trees. The underlying rationale is that both problem classes can be presented as graphs. This fact leads to option of considering a larger spectrum of solutions than those based on the heuristic. Moreover, ant colony optimization algorithms can be used to advantage when building ensembles of classifiers. This book is a combination of a research monograph and a textbook. It can be used in graduate courses, but is also of interest to researchers, both specialists in machine learning and those applying machine learning methods to cope with problems from any field of R & D.

Biologically Inspired Techniques in Many-Criteria Decision Making

Author : Satchidananda Dehuri
Publisher : Springer Nature
ISBN 13 : 3030390330
Total Pages : 268 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Biologically Inspired Techniques in Many-Criteria Decision Making by : Satchidananda Dehuri

Download or read book Biologically Inspired Techniques in Many-Criteria Decision Making written by Satchidananda Dehuri and published by Springer Nature. This book was released on 2020-01-21 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses many-criteria decision-making (MCDM), a process used to find a solution in an environment with several criteria. In many real-world problems, there are several different objectives that need to be taken into account. Solving these problems is a challenging task and requires careful consideration. In real applications, often simple and easy to understand methods are used; as a result, the solutions accepted by decision makers are not always optimal solutions. On the other hand, algorithms that would provide better outcomes are very time consuming. The greatest challenge facing researchers is how to create effective algorithms that will yield optimal solutions with low time complexity. Accordingly, many current research efforts are focused on the implementation of biologically inspired algorithms (BIAs), which are well suited to solving uni-objective problems. This book introduces readers to state-of-the-art developments in biologically inspired techniques and their applications, with a major emphasis on the MCDM process. To do so, it presents a wide range of contributions on e.g. BIAs, MCDM, nature-inspired algorithms, multi-criteria optimization, machine learning and soft computing.

Evolutionary Decision Trees in Large-Scale Data Mining

Author : Marek Kretowski
Publisher : Springer
ISBN 13 : 3030218511
Total Pages : 180 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Evolutionary Decision Trees in Large-Scale Data Mining by : Marek Kretowski

Download or read book Evolutionary Decision Trees in Large-Scale Data Mining written by Marek Kretowski and published by Springer. This book was released on 2019-06-05 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a unified framework, based on specialized evolutionary algorithms, for the global induction of various types of classification and regression trees from data. The resulting univariate or oblique trees are significantly smaller than those produced by standard top-down methods, an aspect that is critical for the interpretation of mined patterns by domain analysts. The approach presented here is extremely flexible and can easily be adapted to specific data mining applications, e.g. cost-sensitive model trees for financial data or multi-test trees for gene expression data. The global induction can be efficiently applied to large-scale data without the need for extraordinary resources. With a simple GPU-based acceleration, datasets composed of millions of instances can be mined in minutes. In the event that the size of the datasets makes the fastest memory computing impossible, the Spark-based implementation on computer clusters, which offers impressive fault tolerance and scalability potential, can be applied.

Advanced Machine Learning with Evolutionary and Metaheuristic Techniques

Author : Jayaraman Valadi
Publisher : Springer Nature
ISBN 13 : 9819997186
Total Pages : 365 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Advanced Machine Learning with Evolutionary and Metaheuristic Techniques by : Jayaraman Valadi

Download or read book Advanced Machine Learning with Evolutionary and Metaheuristic Techniques written by Jayaraman Valadi and published by Springer Nature. This book was released on with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Ant Colony Optimization

Author : Marco Dorigo
Publisher : MIT Press
ISBN 13 : 9780262042192
Total Pages : 324 pages
Book Rating : 4.0/5 (421 download)

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Book Synopsis Ant Colony Optimization by : Marco Dorigo

Download or read book Ant Colony Optimization written by Marco Dorigo and published by MIT Press. This book was released on 2004-06-04 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of the rapidly growing field of ant colony optimization that describes theoretical findings, the major algorithms, and current applications. The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses. The book first describes the translation of observed ant behavior into working optimization algorithms. The ant colony metaheuristic is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for the network routing problem, is described in detail. The authors conclude by summarizing the progress in the field and outlining future research directions. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises. Ant Colony Optimization will be of interest to academic and industry researchers, graduate students, and practitioners who wish to learn how to implement ACO algorithms.

Machine Learning-Based Modelling in Atomic Layer Deposition Processes

Author : Oluwatobi Adeleke
Publisher : CRC Press
ISBN 13 : 1003803334
Total Pages : 353 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Machine Learning-Based Modelling in Atomic Layer Deposition Processes by : Oluwatobi Adeleke

Download or read book Machine Learning-Based Modelling in Atomic Layer Deposition Processes written by Oluwatobi Adeleke and published by CRC Press. This book was released on 2023-12-15 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: While thin film technology has benefited greatly from artificial intelligence (AI) and machine learning (ML) techniques, there is still much to be learned from a full-scale exploration of these technologies in atomic layer deposition (ALD). This book provides in-depth information regarding the application of ML-based modeling techniques in thin film technology as a standalone approach and integrated with the classical simulation and modeling methods. It is the first of its kind to present detailed information regarding approaches in ML-based modeling, optimization, and prediction of the behaviors and characteristics of ALD for improved process quality control and discovery of new materials. As such, this book fills significant knowledge gaps in the existing resources as it provides extensive information on ML and its applications in film thin technology. Offers an in-depth overview of the fundamentals of thin film technology, state-of-the-art computational simulation approaches in ALD, ML techniques, algorithms, applications, and challenges. Establishes the need for and significance of ML applications in ALD while introducing integration approaches for ML techniques with computation simulation approaches. Explores the application of key techniques in ML, such as predictive analysis, classification techniques, feature engineering, image processing capability, and microstructural analysis of deep learning algorithms and generative model benefits in ALD. Helps readers gain a holistic understanding of the exciting applications of ML-based solutions to ALD problems and apply them to real-world issues. Aimed at materials scientists and engineers, this book fills significant knowledge gaps in existing resources as it provides extensive information on ML and its applications in film thin technology. It also opens space for future intensive research and intriguing opportunities for ML-enhanced ALD processes, which scale from academic to industrial applications. . .

Computational Collective Intelligence

Author : Ngoc Thanh Nguyen
Publisher : Springer Nature
ISBN 13 : 3030880818
Total Pages : 817 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Computational Collective Intelligence by : Ngoc Thanh Nguyen

Download or read book Computational Collective Intelligence written by Ngoc Thanh Nguyen and published by Springer Nature. This book was released on 2021-09-29 with total page 817 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th International Conference on Computational Collective Intelligence, ICCCI 2021, held in September/October 2021. The conference was held virtually due to the COVID-19 pandemic. The 58 full papers were carefully reviewed and selected from 230 submissions. The papers are grouped in topical issues on knowledge engineering and semantic web; social networks and recommender systems; collective decision-making; cooperative strategies for decision making and optimization; data mining and machine learning; computer vision techniques; natural language processing; Internet of Things: technologies and applications; Internet of Things and computational technologies for collective intelligence; computational intelligence for multimedia understanding.

Modern Optimization Techniques for Smart Grids

Author : Adel Ali Abou El-Ela
Publisher : Springer Nature
ISBN 13 : 3030960250
Total Pages : 237 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Modern Optimization Techniques for Smart Grids by : Adel Ali Abou El-Ela

Download or read book Modern Optimization Techniques for Smart Grids written by Adel Ali Abou El-Ela and published by Springer Nature. This book was released on 2022-09-15 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern Optimization Techniques for Smart Grids presents current research and methods for monitoring transmission systems and enhancing distribution system performance using optimization techniques considering the role of different single and multi-objective functions. The authors present in-depth information on integrated systems for smart transmission and distribution, including using smart meters such as phasor measurement units (PMUs), enhancing distribution system performance using the optimal placement of distributed generations (DGs) and/or capacitor banks, and optimal capacitor placement for power loss reduction and voltage profile improvement. The book will be a valuable reference for researchers, students, and engineers working in electrical power engineering and renewable energy systems. Predicts future development of hybrid power systems; Introduces enhanced optimization strategies; Includes MATLAB M-file codes.

Data Mining with Decision Trees

Author : Lior Rokach
Publisher : World Scientific
ISBN 13 : 9812771719
Total Pages : 263 pages
Book Rating : 4.8/5 (127 download)

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Book Synopsis Data Mining with Decision Trees by : Lior Rokach

Download or read book Data Mining with Decision Trees written by Lior Rokach and published by World Scientific. This book was released on 2008 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first comprehensive book dedicated entirely to the field of decision trees in data mining and covers all aspects of this important technique.Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining, the science and technology of exploring large and complex bodies of data in order to discover useful patterns. The area is of great importance because it enables modeling and knowledge extraction from the abundance of data available. Both theoreticians and practitioners are continually seeking techniques to make the process more efficient, cost-effective and accurate. Decision trees, originally implemented in decision theory and statistics, are highly effective tools in other areas such as data mining, text mining, information extraction, machine learning, and pattern recognition. This book invites readers to explore the many benefits in data mining that decision trees offer: Self-explanatory and easy to follow when compacted Able to handle a variety of input data: nominal, numeric and textual Able to process datasets that may have errors or missing values High predictive performance for a relatively small computational effort Available in many data mining packages over a variety of platforms Useful for various tasks, such as classification, regression, clustering and feature selection

Advances in Information, Communication and Cybersecurity

Author : Yassine Maleh
Publisher : Springer Nature
ISBN 13 : 303091738X
Total Pages : 621 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Advances in Information, Communication and Cybersecurity by : Yassine Maleh

Download or read book Advances in Information, Communication and Cybersecurity written by Yassine Maleh and published by Springer Nature. This book was released on 2022-01-12 with total page 621 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the proceedings of the International Conference on Information, Communication and Cybersecurity, held on November 10–11, 2021, in Khouribga, Morocco. The conference was jointly coorganized by The National School of Applied Sciences of Sultan Moulay Slimane University, Morocco, and Charles Darwin University, Australia. This book provides an opportunity to account for state-of-the-art works, future trends impacting information technology, communications, and cybersecurity, focusing on elucidating the challenges, opportunities, and inter-dependencies that are just around the corner. This book is helpful for students and researchers as well as practitioners. ICI2C 2021 was devoted to advances in smart information technologies, communication, and cybersecurity. It was considered a meeting point for researchers and practitioners to implement advanced information technologies into various industries. There were 159 paper submissions from 24 countries. Each submission was reviewed by at least three chairs or PC members. We accepted 54 regular papers (34\%). Unfortunately, due to limitations of conference topics and edited volumes, the Program Committee was forced to reject some interesting papers, which did not satisfy these topics or publisher requirements. We would like to thank all authors and reviewers for their work and valuable contributions. The friendly and welcoming attitude of conference supporters and contributors made this event a success!

Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks

Author : Raj, Alex Noel Joseph
Publisher : IGI Global
ISBN 13 : 1668445603
Total Pages : 293 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks by : Raj, Alex Noel Joseph

Download or read book Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks written by Raj, Alex Noel Joseph and published by IGI Global. This book was released on 2022-06-24 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is crucial that forensic science meets challenges such as identifying hidden patterns in data, validating results for accuracy, and understanding varying criminal activities in order to be authoritative so as to hold up justice and public safety. Artificial intelligence, with its potential subsets of machine learning and deep learning, has the potential to transform the domain of forensic science by handling diverse data, recognizing patterns, and analyzing, interpreting, and presenting results. Machine Learning and deep learning frameworks, with developed mathematical and computational tools, facilitate the investigators to provide reliable results. Further study on the potential uses of these technologies is required to better understand their benefits. Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks provides an outline of deep learning and machine learning frameworks and methods for use in forensic science to produce accurate and reliable results to aid investigation processes. The book also considers the challenges, developments, advancements, and emerging approaches of deep learning and machine learning. Covering key topics such as biometrics, augmented reality, and fraud investigation, this reference work is crucial for forensic scientists, law enforcement, computer scientists, researchers, scholars, academicians, practitioners, instructors, and students.

Marketing Analytics: Creating Customer Centric Culture

Author : Joseph B. Rivera
Publisher : Joseph B. Rivera
ISBN 13 :
Total Pages : 189 pages
Book Rating : 4./5 ( download)

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Book Synopsis Marketing Analytics: Creating Customer Centric Culture by : Joseph B. Rivera

Download or read book Marketing Analytics: Creating Customer Centric Culture written by Joseph B. Rivera and published by Joseph B. Rivera. This book was released on 2020-02-17 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: A game-changing approach to marketing by an experienced author, speaker and businessman Joseph B. Rivera. Joseph B. Rivera has first-hand experience in business. He has learned everything through hard work and perseverance, and has inspired quite a lot of entrepreneurs, businessmen, executives, employees, and business students to challenge themselves in this modern era of commerce. For the first time, Joseph B. Rivera offers his years of experience and wisdom in this one compact, very accessible and enduring masterpiece. MARKETING ANALYTICS: CREATING CUSTOMER-CENTRIC CULTURE helps you to create a transformative culture toward excellence in your business. Whether you are an executive, businessman, business owner, investor, marketer, trainer, speaker or a student of marketing, you will be proud of what you will learn. When applied right, you will change the way products and services are designed, created and offered to the world. This book teaches you how to meaningfully connect emotionally and practically to your consumers. Remember, it is not just all about the money. Here, Joseph has put together his passion, insights, observation and experience to mentor you: ✔️How to understand the needs of the market. ✔️How to position your business. ✔️How to overcome competition. ✔️How to revolutionize your business. Learn the art or marketing analytics, and be a game changer.

Advances in Machine Learning/Deep Learning-based Technologies

Author : George A. Tsihrintzis
Publisher : Springer Nature
ISBN 13 : 3030767949
Total Pages : 237 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Advances in Machine Learning/Deep Learning-based Technologies by : George A. Tsihrintzis

Download or read book Advances in Machine Learning/Deep Learning-based Technologies written by George A. Tsihrintzis and published by Springer Nature. This book was released on 2021-08-05 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the 4th Industrial Revolution is restructuring human societal organization into, so-called, “Society 5.0”, the field of Machine Learning (and its sub-field of Deep Learning) and related technologies is growing continuously and rapidly, developing in both itself and towards applications in many other disciplines. Researchers worldwide aim at incorporating cognitive abilities into machines, such as learning and problem solving. When machines and software systems have been enhanced with Machine Learning/Deep Learning components, they become better and more efficient at performing specific tasks. Consequently, Machine Learning/Deep Learning stands out as a research discipline due to its worldwide pace of growth in both theoretical advances and areas of application, while achieving very high rates of success and promising major impact in science, technology and society. The book at hand aims at exposing its readers to some of the most significant Advances in Machine Learning/Deep Learning-based Technologies. The book consists of an editorial note and an additional ten (10) chapters, all invited from authors who work on the corresponding chapter theme and are recognized for their significant research contributions. In more detail, the chapters in the book are organized into five parts, namely (i) Machine Learning/Deep Learning in Socializing and Entertainment, (ii) Machine Learning/Deep Learning in Education, (iii) Machine Learning/Deep Learning in Security, (iv) Machine Learning/Deep Learning in Time Series Forecasting, and (v) Machine Learning in Video Coding and Information Extraction. This research book is directed towards professors, researchers, scientists, engineers and students in Machine Learning/Deep Learning-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of the most recent Machine Learning/Deep Learning-based technologies. An extensive list of bibliographic references at the end of each chapter guides the readers to probe further into the application areas of interest to them.

Handbook Of Machine Learning - Volume 2: Optimization And Decision Making

Author : Tshilidzi Marwala
Publisher : World Scientific
ISBN 13 : 981120568X
Total Pages : 321 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Handbook Of Machine Learning - Volume 2: Optimization And Decision Making by : Tshilidzi Marwala

Download or read book Handbook Of Machine Learning - Volume 2: Optimization And Decision Making written by Tshilidzi Marwala and published by World Scientific. This book was released on 2019-11-21 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building on , this volume on Optimization and Decision Making covers a range of algorithms and their applications. Like the first volume, it provides a starting point for machine learning enthusiasts as a comprehensive guide on classical optimization methods. It also provides an in-depth overview on how artificial intelligence can be used to define, disprove or validate economic modeling and decision making concepts.

Machine Learning, Big Data, and IoT for Medical Informatics

Author : Pardeep Kumar
Publisher : Academic Press
ISBN 13 : 0128217812
Total Pages : 458 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Machine Learning, Big Data, and IoT for Medical Informatics by : Pardeep Kumar

Download or read book Machine Learning, Big Data, and IoT for Medical Informatics written by Pardeep Kumar and published by Academic Press. This book was released on 2021-06-13 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics. In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data. This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT. Explains the uses of CNN, Deep Learning and extreme machine learning concepts for the design and development of predictive diagnostic systems. Includes several privacy preservation techniques for medical data. Presents the integration of Internet of Things with predictive diagnostic systems for disease diagnosis. Offers case studies and applications relating to machine learning, big data, and health care analysis.

Intelligent Information and Database Systems

Author : Ngoc-Thanh Nguyen
Publisher : Springer
ISBN 13 : 3319054589
Total Pages : 618 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Intelligent Information and Database Systems by : Ngoc-Thanh Nguyen

Download or read book Intelligent Information and Database Systems written by Ngoc-Thanh Nguyen and published by Springer. This book was released on 2014-02-28 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 8397 and LNAI 8398 constitutes the refereed proceedings of the 6th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2014, held in Bangkok, Thailand in April 2014. The 125 revised papers presented were carefully reviewed and selected from 300 submissions. Suggestion: The aim of the conference is to provide an internationally respected forum for scientific research in the technologies and applications of intelligent information and database systems. The papers are organized in topical sections on Natural Language and Text Processing, Intelligent Information Retrieval, Semantic Web, Social Networks and Recommendation Systems, Intelligent Database Systems, Decision Support Systems, Computer Vision Techniques, Machine Learning and Data Mining, Multiple Model Approach to Machine Learning, MMAML 2014, Computational Intelligence, CI 2014, Engineering Knowledge and Semantic Systems , IWEKSS 2014, Innovations in Intelligent Computation and Applications, IICA 2014, Modelling and Optimization Techniques in Information Systems, Database Systems and Industrial Systems, MOT 2014, Innovation via Collective Intelligences and Globalization in Business Management, ICIGBM 2014, Intelligent Supply Chains, ISC 2014, and Human Motion: Acquisition, Processing, Analysis, Synthesis and Visualization for Massive Datasets, HMMD 2014.