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In this book authors study special type of subset vertex multi subgraphs; these multi subgraphs can be directed or otherwise. Another special feature of these subset vertex multigraphs is that we are aware of the elements in each vertex set and how it affects the structure of both subset vertex multisubgraphs and edge multisubgraphs. It is pertinent to record at this juncture that certain ego centric directed multistar graphs become empty on the removal of one edge, there by theorising the importance, and giving certain postulates how to safely form ego centric multi networks.
In this book authors introduce the notion of subset vertex multigraphs for the first time. The study of subset vertex graphs was introduced in 2018, however they are not multiedged, further they were unique once the vertex subsets are given. These subset vertex multigraphs are also unique once the vertex subsets are given and the added advantage is that the number of common elements between two vertex subsets accounts for the number of edges between them, when there is no common element there is no edge between them.
In this book any network which can be represented as a multigraph is referred to as a multi network. Several properties of multigraphs have been described and developed in this book. When multi path or multi walk or multi trail is considered in a multigraph, it is seen that there can be many multi walks, and so on between any two nodes and this makes multigraphs very different.
The plithogenic set is a generalization of crisp, fuzzy, intuitionistic fuzzy, and Neutrosophic sets, it is a set whose elements are characterized by many attributes' values. This book gives some possible applications of plithogenic sets defined by Florentin Smarandache (2018). The authors have defined a new class of special type of graphs which can be applied for plithogenic models.
This book constitutes the refereed conference proceedings of the 10th International Conference on Algorithms and Complexity, CIAC 2017, held in Athens, Greece, in May 2017. The 36 revised full papers were carefully reviewed and selected from 90 submissions and are presented together with 3 abstracts of invited talks and a paper to the 70th birthday of Stathis Zachos. The papers present original research in the theory and applications of algorithms and computational complexity.
This book constitutes the refereed post-conference proceedings of the 29th International Workshop on Combinatorial Algorithms, IWOCA 2018, held in Singapore, Singapore, in July 2018. The 31 regular papers presented in this volume were carefully reviewed and selected from 69 submissions. They cover diverse areas of combinatorical algorithms, complexity theory, graph theory and combinatorics, combinatorial optimization, cryptography and information security, algorithms on strings and graphs, graph drawing and labelling, computational algebra and geometry, computational biology, probabilistic and randomised algorithms, algorithms for big data analytics, and new paradigms of computation.
Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Properties of Social Networks, Algorithms for Structural Discovery of Social Networks and Content Analysis in Social Networks. This book is also unique in focussing on the data analytical aspects of social networks in the internet scenario, rather than the traditional sociology-driven emphasis prevalent in the existing books, which do not focus on the unique data-intensive characteristics of online social networks. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book. This book targets advanced level students and researchers concentrating on computer science as a secondary text or reference book. Data mining, database, information security, electronic commerce and machine learning professionals will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science.
Welcome to "Data Structures with Go: A Comprehensive Guide," your gateway to mastering data structures using the Go programming language. In today’s fast-paced software development world, a solid grasp of data structures is essential for creating efficient, scalable, and high-performance applications. This book provides a thorough exploration of data structures through Go, a language known for its simplicity, performance, and robust concurrency support. Why This Book? Data structures are fundamental to computer science and software engineering. They determine how data is organized, stored, and manipulated, significantly impacting the performance and efficiency of algorithms. With Go’s growing popularity for its clean syntax and effective concurrency model, it is an excellent choice for learning and implementing data structures. This book leverages Go’s features to offer practical insights into data structures, making it a valuable resource for developers of all skill levels. What You Will Learn Fundamentals of Data Structures: The book starts with an introduction to data structures, highlighting their importance and role in software development. You’ll explore basic data types in Go and their applications in various data structures. Arrays and Slices: Delve into arrays and slices, foundational structures in Go. Learn how to declare, initialize, and manipulate them, and understand their performance implications and practical uses. Linked Lists: Explore singly and doubly linked lists, including their structures, operations, and Go implementations. Understand how linked lists compare to arrays and slices and their advantages and limitations. Stacks and Queues: Study these essential linear data structures. Learn about stack (LIFO) and queue (FIFO) operations and their implementations in Go. The chapter also covers variants like deques and priority queues. Trees: Understand hierarchical data structures such as binary trees, binary search trees (BST), AVL trees, and Red-Black trees. Learn about tree operations, traversal techniques, and their Go implementations. Graphs: Learn about graph representations, including adjacency matrices and adjacency lists, and explore directed and undirected graphs. This chapter also covers common algorithms like Depth-First Search (DFS) and Breadth-First Search (BFS). Hashing: Discover hashing techniques, hash tables, and collision handling strategies. Implement hash tables in Go and understand their practical applications. Advanced Data Structures: Dive into specialized data structures such as heaps, tries, suffix trees, and Bloom filters. Learn about their implementations and use cases. Algorithms and Data Structures in Practice: Apply data structures to real-world problems. This chapter focuses on sorting and searching algorithms, optimization techniques, and performance profiling in Go. Real-World Applications: Explore how data structures are used in practical projects. Study case studies, best practices, and design patterns for implementing data structures in Go-based systems. Who Should Read This Book? This book caters to: Beginners: Those new to Go or data structures will find a clear, structured introduction. Intermediate Developers: Readers with some experience can deepen their knowledge and tackle advanced topics. Experienced Professionals: Those looking to explore Go or stay updated with modern practices will find valuable insights and practical examples. Learning Approach Emphasizing hands-on learning, the book includes practical examples, exercises, and real-world case studies to reinforce understanding and encourage experimentation. By working through these exercises, you will gain practical experience and a deeper grasp of data structures in Go. "Data Structures with Go: A Comprehensive Guide" is your key to mastering essential computer science principles and applying them effectively in modern applications. Dive in and discover how Go can enhance your skills in building robust, efficient, and scalable systems. Aditya