graph based clustering and data visualization algorithms springerbriefs in computer science

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Graph Based Clustering And Data Visualization Algorithms

Author : Ágnes Vathy-Fogarassy
ISBN : 9781447151586
Genre : Computers
File Size : 59. 97 MB
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This work presents a data visualization technique that combines graph-based topology representation and dimensionality reduction methods to visualize the intrinsic data structure in a low-dimensional vector space. The application of graphs in clustering and visualization has several advantages. A graph of important edges (where edges characterize relations and weights represent similarities or distances) provides a compact representation of the entire complex data set. This text describes clustering and visualization methods that are able to utilize information hidden in these graphs, based on the synergistic combination of clustering, graph-theory, neural networks, data visualization, dimensionality reduction, fuzzy methods, and topology learning. The work contains numerous examples to aid in the understanding and implementation of the proposed algorithms, supported by a MATLAB toolbox available at an associated website.

Interactive Segmentation Techniques

Author : Jia He
ISBN : 9789814451604
Genre : Technology & Engineering
File Size : 77. 61 MB
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This book focuses on interactive segmentation techniques, which have been extensively studied in recent decades. Interactive segmentation emphasizes clear extraction of objects of interest, whose locations are roughly indicated by human interactions based on high level perception. This book will first introduce classic graph-cut segmentation algorithms and then discuss state-of-the-art techniques, including graph matching methods, region merging and label propagation, clustering methods, and segmentation methods based on edge detection. A comparative analysis of these methods will be provided with quantitative and qualitative performance evaluation, which will be illustrated using natural and synthetic images. Also, extensive statistical performance comparisons will be made. Pros and cons of these interactive segmentation methods will be pointed out, and their applications will be discussed. There have been only a few surveys on interactive segmentation techniques, and those surveys do not cover recent state-of-the art techniques. By providing comprehensive up-to-date survey on the fast developing topic and the performance evaluation, this book can help readers learn interactive segmentation techniques quickly and thoroughly.

Explaining Algorithms Using Metaphors

Author : Michal Forišek
ISBN : 9781447150190
Genre : Education
File Size : 45. 78 MB
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There is a significant difference between designing a new algorithm, proving its correctness, and teaching it to an audience. When teaching algorithms, the teacher's main goal should be to convey the underlying ideas and to help the students form correct mental models related to the algorithm. This process can often be facilitated by using suitable metaphors. This work provides a set of novel metaphors identified and developed as suitable tools for teaching many of the "classic textbook" algorithms taught in undergraduate courses worldwide. Each chapter provides exercises and didactic notes for teachers based on the authors’ experiences when using the metaphor in a classroom setting.

Visualizing The Data City

Author : Paolo Ciuccarelli
ISBN : 9783319021959
Genre : Computers
File Size : 71. 58 MB
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This book investigates novel methods and technologies for the collection, analysis and representation of real-time user-generated data at the urban scale in order to explore potential scenarios for more participatory design, planning and management processes. For this purpose, the authors present a set of experiments conducted in collaboration with urban stakeholders at various levels (including citizens, city administrators, urban planners, local industries and NGOs) in Milan and New York in 2012. It is examined whether geo-tagged and user-generated content can be of value in the creation of meaningful, real-time indicators of urban quality, as it is perceived and communicated by the citizens. The meanings that people attach to places are also explored to discover what such an urban semantic layer looks like and how it unfolds over time. As a conclusion, recommendations are proposed for the exploitation of user-generated content in order to answer hitherto unsolved urban questions. Readers will find in this book a fascinating exploration of techniques for mining the social web that can be applied to procure user-generated content as a means of investigating urban dynamics.

Automatic Design Of Decision Tree Induction Algorithms

Author : Rodrigo C. Barros
ISBN : 9783319142319
Genre : Computers
File Size : 26. 7 MB
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Presents a detailed study of the major design components that constitute a top-down decision-tree induction algorithm, including aspects such as split criteria, stopping criteria, pruning and the approaches for dealing with missing values. Whereas the strategy still employed nowadays is to use a 'generic' decision-tree induction algorithm regardless of the data, the authors argue on the benefits that a bias-fitting strategy could bring to decision-tree induction, in which the ultimate goal is the automatic generation of a decision-tree induction algorithm tailored to the application domain of interest. For such, they discuss how one can effectively discover the most suitable set of components of decision-tree induction algorithms to deal with a wide variety of applications through the paradigm of evolutionary computation, following the emergence of a novel field called hyper-heuristics. "Automatic Design of Decision-Tree Induction Algorithms" would be highly useful for machine learning and evolutionary computation students and researchers alike.

Redescription Mining

Author : Esther Galbrun
ISBN : 9783319728896
Genre : Computers
File Size : 76. 32 MB
Format : PDF
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This book provides a gentle introduction to redescription mining, a versatile data mining tool that is useful to find distinct common characterizations of the same objects and, vice versa, to identify sets of objects that admit multiple shared descriptions. It is intended for readers who are familiar with basic data analysis techniques such as clustering, frequent itemset mining, and classification. Redescription mining is defined in a general way, making it applicable to different types of data. The general framework is made more concrete through many practical examples that show the versatility of redescription mining. The book also introduces the main algorithmic ideas for mining redescriptions, together with applications from various domains. The final part of the book contains variations and extensions of the basic redescription mining problem, and discusses some future directions and open questions.

Apache Spark Graph Processing

Author : Rindra Ramamonjison
ISBN : 9781784398958
Genre : Computers
File Size : 27. 27 MB
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Build, process and analyze large-scale graph data effectively with Spark About This Book Find solutions for every stage of data processing from loading and transforming graph data to Improve the scalability of your graphs with a variety of real-world applications with complete Scala code. A concise guide to processing large-scale networks with Apache Spark. Who This Book Is For This book is for data scientists and big data developers who want to learn the processing and analyzing graph datasets at scale. Basic programming experience with Scala is assumed. Basic knowledge of Spark is assumed. What You Will Learn Write, build and deploy Spark applications with the Scala Build Tool. Build and analyze large-scale network datasets Analyze and transform graphs using RDD and graph-specific operations Implement new custom graph operations tailored to specific needs. Develop iterative and efficient graph algorithms using message aggregation and Pregel abstraction Extract subgraphs and use it to discover common clusters Analyze graph data and solve various data science problems using real-world datasets. In Detail Apache Spark is the next standard of open-source cluster-computing engine for processing big data. Many practical computing problems concern large graphs, like the Web graph and various social networks. The scale of these graphs - in some cases billions of vertices, trillions of edges - poses challenges to their efficient processing. Apache Spark GraphX API combines the advantages of both data-parallel and graph-parallel systems by efficiently expressing graph computation within the Spark data-parallel framework. This book will teach the user to do graphical programming in Apache Spark, apart from an explanation of the entire process of graphical data analysis. You will journey through the creation of graphs, its uses, its exploration and analysis and finally will also cover the conversion of graph elements into graph structures. This book begins with an introduction of the Spark system, its libraries and the Scala Build Tool. Using a hands-on approach, this book will quickly teach you how to install and leverage Spark interactively on the command line and in a standalone Scala program. Then, it presents all the methods for building Spark graphs using illustrative network datasets. Next, it will walk you through the process of exploring, visualizing and analyzing different network characteristics. This book will also teach you how to transform raw datasets into a usable form. In addition, you will learn powerful operations that can be used to transform graph elements and graph structures. Furthermore, this book also teaches how to create custom graph operations that are tailored for specific needs with efficiency in mind. The later chapters of this book cover more advanced topics such as clustering graphs, implementing graph-parallel iterative algorithms and learning methods from graph data. Style and approach A step-by-step guide that will walk you through the key ideas and techniques for processing big graph data at scale, with practical examples that will ensure an overall understanding of the concepts of Spark.

Computational Movement Analysis

Author : Patrick Laube
ISBN : 9783319102689
Genre : Computers
File Size : 77. 27 MB
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This SpringerBrief discusses the characteristics of spatiotemporal movement data, including uncertainty and scale. It investigates three core aspects of Computational Movement Analysis: Conceptual modeling of movement and movement spaces, spatiotemporal analysis methods aiming at a better understanding of movement processes (with a focus on data mining for movement patterns), and using decentralized spatial computing methods in movement analysis. The author presents Computational Movement Analysis as an interdisciplinary umbrella for analyzing movement processes with methods from a range of fields including GIScience, spatiotemporal databases and data mining. Key challenges in Computational Movement Analysis include bridging the semantic gap, privacy issues when movement data involves people, incorporating big and open data, and opportunities for decentralized movement analysis arising from the internet of things. The interdisciplinary concepts of Computational Movement Analysis make this an important book for professionals and students in computer science, geographic information science and its application areas, especially movement ecology and transportation research.

Community Oriented Policing And Technological Innovations

Author : Georgios Leventakis
ISBN : 9783319892948
Genre : Social Science
File Size : 33. 89 MB
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This Brief presents new approaches and innovative challenges to address bringing technology into community-oriented policing efforts. “Community-oriented policing” is an approach that encourages police to develop and maintain personal relationships with citizens and community organizations. By developing these partnerships, the goal is to enhance trust and legitimacy of police by the community (and vice versa), and focus on engaging the community crime prevention and detection efforts for sustainable, long-term crime reduction. The contributions to this volume emphasize how technological innovations can advance community-oriented policing goals, such as: -Strengthening community policing principles through effective and efficient tools, procedures and approaches - Accelerating communication between citizens and police forces - Early identification, timely intervention, as well as better crime reporting, identification of risks, unreported and undiscovered crime through the community Contributions to this volume were developed out of the Next Generation Community Policing (NGCP) International Conference was co-organized by nine contributing research and development projects, funded by the Horizon 2020 SECURITY Program of the European Commission. It will be of interest to researchers in criminology and criminal justice, as well as related fields such as sociology, public health, security, IT and public policy. This book is open access under a CC BY license.

Proceedings Of The International Conference On Computing And Communication Systems

Author : J. K. Mandal
ISBN : 9789811068904
Genre : Technology & Engineering
File Size : 78. 96 MB
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The volume contains latest research work presented at International Conference on Computing and Communication Systems (I3CS 2016) held at North Eastern Hill University (NEHU), Shillong, India. The book presents original research results, new ideas and practical development experiences which concentrate on both theory and practices. It includes papers from all areas of information technology, computer science, electronics and communication engineering written by researchers, scientists, engineers and scholar students and experts from India and abroad.

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