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Special Subset Vertex Subgraphs for Social Networks

Special Subset Vertex Subgraphs for Social Networks PDF Author: W. B. Vasantha Kandasamy
Publisher: Infinite Study
ISBN: 1599735636
Category : Mathematics
Languages : en
Pages : 288

Book Description
In this book authors for the first time introduce the new notion of special subset vertex subgraph of subset vertex graphs introduced recently. These subset vertex graphs takes the vertex set values from the power set P(X) of any set X. The main speciality of these subset vertex graphs is that once a set of subsets from P(X) is given, the edges of the graph are fixed in a unique way, so for a given collection of subset vertices the graph is always unique.

Special Subset Vertex Subgraphs for Social Networks

Special Subset Vertex Subgraphs for Social Networks PDF Author: W. B. Vasantha Kandasamy
Publisher: Infinite Study
ISBN: 1599735636
Category : Mathematics
Languages : en
Pages : 288

Book Description
In this book authors for the first time introduce the new notion of special subset vertex subgraph of subset vertex graphs introduced recently. These subset vertex graphs takes the vertex set values from the power set P(X) of any set X. The main speciality of these subset vertex graphs is that once a set of subsets from P(X) is given, the edges of the graph are fixed in a unique way, so for a given collection of subset vertices the graph is always unique.

Subset Vertex Graphs for Social Networks

Subset Vertex Graphs for Social Networks PDF Author: W. B. Vasantha Kandasamy
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 290

Book Description
Social information networks concept was introduced or perceived by researchers Emile Durkheim and Ferdinand Tonnies as social groups as early as 1890’s . However Tonnies argued that social groups can exist as personal and direct social ties that either link individuals who share values and beliefs or impersonal, formal and instrumental social links but Durkheim gave a non individualistic explanation of social facts arguing that social phenomena arise when interacting individuals constitute a reality that can no longer be accounted for in terms of the properties of individual actors. Georg Simmel analyzed the network size on interaction and examined and likelihood of interaction in loosely knit networks rather than groups.

Special Subset Vertex Multisubgraphs for Multi Networks

Special Subset Vertex Multisubgraphs for Multi Networks PDF Author: W. B. Vasantha Kandasamy, Ilanthenral K, Florentin Smarandache
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 253

Book Description
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.

Subset Vertex Multigraphs and Neutrosophic Multigraphs for Social Multi Networks

Subset Vertex Multigraphs and Neutrosophic Multigraphs for Social Multi Networks PDF Author: W. B. Vasantha Kandasamy
Publisher: Infinite Study
ISBN: 1599736020
Category : Mathematics
Languages : en
Pages : 296

Book Description
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.

Multigraphs for Multi Networks

Multigraphs for Multi Networks PDF Author: W. B. Vasantha Kandasamy
Publisher: Infinite Study
ISBN: 1599736012
Category : Mathematics
Languages : en
Pages : 318

Book Description
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.

SPECIAL SUBSET VERTEX MULTISUBGRAPHS FOR MULTI NETWORKS

SPECIAL SUBSET VERTEX MULTISUBGRAPHS FOR MULTI NETWORKS PDF Author: W. B. VASANTHA. KANDASAMY
Publisher:
ISBN: 9781599736334
Category : Graph theory
Languages : en
Pages :

Book Description


Plithogenic Graphs

Plithogenic Graphs PDF Author: W. B. Vasantha Kandasamy
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 296

Book Description
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.

Anonymizing Subsets of Social Networks

Anonymizing Subsets of Social Networks PDF Author: Jared Glen Gaertner
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description
In recent years, concerns of privacy have become more prominent for social networks. Anonymizing a graph meaningfully is a challenging problem, as the original graph properties must be preserved as well as possible. We introduce a generalization of the degree anonymization problem posed by Liu and Terzi. In this problem, our goal is to anonymize a given subset of vertices in a graph while adding the fewest possible number of edges. We examine different approaches to solving the problem, one of which finds a degree-constrained subgraph to determine which edges to add within the given subset and another that uses a greedy approach that is not optimal, but is more efficient in space and time. The main contribution of this thesis is an efficient algorithm for this problem by exploring its connection with the degree-constrained subgraph problem. Our experimental results show that our algorithms perform very well on many instances of social network data.

Formal Concept Analysis of Social Networks

Formal Concept Analysis of Social Networks PDF Author: Rokia Missaoui
Publisher: Springer
ISBN: 3319641670
Category : Computers
Languages : en
Pages : 210

Book Description
The book studies the existing and potential connections between Social Network Analysis (SNA) and Formal Concept Analysis (FCA) by showing how standard SNA techniques, usually based on graph theory, can be supplemented by FCA methods, which rely on lattice theory. The book presents contributions to the following areas: acquisition of terminological knowledge from social networks, knowledge communities, individuality computation, other types of FCA-based analysis of bipartite graphs (two-mode networks), multimodal clustering, community detection and description in one-mode and multi-mode networks, adaptation of the dual-projection approach to weighted bipartite graphs, extensions to the Kleinberg's HITS algorithm as well as attributed graph analysis.

Graph Databases in Action

Graph Databases in Action PDF Author: Josh Perryman
Publisher: Simon and Schuster
ISBN: 1638350108
Category : Computers
Languages : en
Pages : 336

Book Description
Graph Databases in Action introduces you to graph database concepts by comparing them with relational database constructs. You'll learn just enough theory to get started, then progress to hands-on development. Discover use cases involving social networking, recommendation engines, and personalization. Summary Relationships in data often look far more like a web than an orderly set of rows and columns. Graph databases shine when it comes to revealing valuable insights within complex, interconnected data such as demographics, financial records, or computer networks. In Graph Databases in Action, experts Dave Bechberger and Josh Perryman illuminate the design and implementation of graph databases in real-world applications. You'll learn how to choose the right database solutions for your tasks, and how to use your new knowledge to build agile, flexible, and high-performing graph-powered applications! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Isolated data is a thing of the past! Now, data is connected, and graph databases—like Amazon Neptune, Microsoft Cosmos DB, and Neo4j—are the essential tools of this new reality. Graph databases represent relationships naturally, speeding the discovery of insights and driving business value. About the book Graph Databases in Action introduces you to graph database concepts by comparing them with relational database constructs. You'll learn just enough theory to get started, then progress to hands-on development. Discover use cases involving social networking, recommendation engines, and personalization. What's inside Graph databases vs. relational databases Systematic graph data modeling Querying and navigating a graph Graph patterns Pitfalls and antipatterns About the reader For software developers. No experience with graph databases required. About the author Dave Bechberger and Josh Perryman have decades of experience building complex data-driven systems and have worked with graph databases since 2014. Table of Contents PART 1 - GETTING STARTED WITH GRAPH DATABASES 1 Introduction to graphs 2 Graph data modeling 3 Running basic and recursive traversals 4 Pathfinding traversals and mutating graphs 5 Formatting results 6 Developing an application PART 2 - BUILDING ON GRAPH DATABASES 7 Advanced data modeling techniques 8 Building traversals using known walks 9 Working with subgraphs PART 3 - MOVING BEYOND THE BASICS 10 Performance, pitfalls, and anti-patterns 11 What's next: Graph analytics, machine learning, and resources