Link Prediction In Social Networks By Neutrosophic Graph

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Link Prediction in Social Networks by Neutrosophic Graph

Author : Rupkumar Mahapatra
Publisher : Infinite Study
ISBN 13 :
Total Pages : 15 pages
Book Rating : 4./5 ( download)

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Book Synopsis Link Prediction in Social Networks by Neutrosophic Graph by : Rupkumar Mahapatra

Download or read book Link Prediction in Social Networks by Neutrosophic Graph written by Rupkumar Mahapatra and published by Infinite Study. This book was released on with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: The computation of link prediction is one of the most important tasks on a social network. Several methods are available in the literature to predict links in networks and RSM index is one of them. The RSM index is applicable in the fuzzy environment and it does not incorporate the notion of falsity and indecency parameters which occur frequently in uncertain environments. In the present method, the behaviors of the common neighbor and the other parameters, like nature of job, location, etc., are considered. In this paper, more parameters are included in the RSM index for making it more flexible and realistic and it is best fitted in the neutrosophic environment. Many important properties are studied for this modified RSM index. A small network from Facebook is considered to illustrate the problem.

A Study On Directed Neutrosophic Social Networks

Author : Yunming Hui
Publisher : Infinite Study
ISBN 13 :
Total Pages : 9 pages
Book Rating : 4./5 ( download)

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Book Synopsis A Study On Directed Neutrosophic Social Networks by : Yunming Hui

Download or read book A Study On Directed Neutrosophic Social Networks written by Yunming Hui and published by Infinite Study. This book was released on with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: Popularity of social networks like Facebook, LinkedIn, Twitter, Instagram, WhatsApp is increasingly increasing day by day. Social network scholars are very much interested to capture the uncertainties of social network. The neutrosophic set is a well known tool to handle and represent uncertainties in information due to indeterminateness or incompleteness. The main approach of our study is to investigate the neutrosophic approach to deal the uncertainties that may exist in social network. In this work, we introduce a neutrosophic model to present the social network using directed neutrosophic graph.

Link Prediction in Social Networks

Author : Srinivas Virinchi
Publisher : Springer
ISBN 13 : 3319289225
Total Pages : 73 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Link Prediction in Social Networks by : Srinivas Virinchi

Download or read book Link Prediction in Social Networks written by Srinivas Virinchi and published by Springer. This book was released on 2016-01-22 with total page 73 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work presents link prediction similarity measures for social networks that exploit the degree distribution of the networks. In the context of link prediction in dense networks, the text proposes similarity measures based on Markov inequality degree thresholding (MIDTs), which only consider nodes whose degree is above a threshold for a possible link. Also presented are similarity measures based on cliques (CNC, AAC, RAC), which assign extra weight between nodes sharing a greater number of cliques. Additionally, a locally adaptive (LA) similarity measure is proposed that assigns different weights to common nodes based on the degree distribution of the local neighborhood and the degree distribution of the network. In the context of link prediction in dense networks, the text introduces a novel two-phase framework that adds edges to the sparse graph to forma boost graph.

Neutrosophic Sets and Systems, vol. 50/2022

Author : Florentin Smarandache
Publisher : Infinite Study
ISBN 13 :
Total Pages : 674 pages
Book Rating : 4./5 ( download)

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Book Synopsis Neutrosophic Sets and Systems, vol. 50/2022 by : Florentin Smarandache

Download or read book Neutrosophic Sets and Systems, vol. 50/2022 written by Florentin Smarandache and published by Infinite Study. This book was released on 2022-06-01 with total page 674 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Neutrosophic Sets and Systems” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc. Neutrosophy is a new branch of philosophy that studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. This theory considers every notion or idea together with its opposite or negation and with their spectrum of neutralities in between them (i.e. notions or ideas supporting neither nor ). The and ideas together are referred to as . Neutrosophy is a generalization of Hegel's dialectics (the last one is based on and only). According to this theory every idea tends to be neutralized and balanced by and ideas - as a state of equilibrium. In a classical way , , are disjoint two by two. But, since in many cases the borders between notions are vague, imprecise, Sorites, it is possible that , , (and of course) have common parts two by two, or even all three of them as well. Neutrosophic Set and Neutrosophic Logic are generalizations of the fuzzy set and respectively fuzzy logic (especially of intuitionistic fuzzy set and respectively intuitionistic fuzzy logic).

Link Prediction in Social Networks

Author : Alon Bar Tal
Publisher :
ISBN 13 :
Total Pages : 172 pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis Link Prediction in Social Networks by : Alon Bar Tal

Download or read book Link Prediction in Social Networks written by Alon Bar Tal and published by . This book was released on 2009 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Neutrosophic Sets and Systems, vol. 49/2022

Author : Florentin Smarandache
Publisher : Infinite Study
ISBN 13 :
Total Pages : 611 pages
Book Rating : 4./5 ( download)

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Book Synopsis Neutrosophic Sets and Systems, vol. 49/2022 by : Florentin Smarandache

Download or read book Neutrosophic Sets and Systems, vol. 49/2022 written by Florentin Smarandache and published by Infinite Study. This book was released on 2022-04-01 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Neutrosophic Sets and Systems” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc. Neutrosophy is a new branch of philosophy that studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. This theory considers every notion or idea together with its opposite or negation and with their spectrum of neutralities in between them (i.e. notions or ideas supporting neither nor ). The and ideas together are referred to as . Neutrosophy is a generalization of Hegel's dialectics (the last one is based on and only). According to this theory every idea tends to be neutralized and balanced by and ideas - as a state of equilibrium. In a classical way , , are disjoint two by two. But, since in many cases the borders between notions are vague, imprecise, Sorites, it is possible that , , (and of course) have common parts two by two, or even all three of them as well. Neutrosophic Set and Neutrosophic Logic are generalizations of the fuzzy set and respectively fuzzy logic (especially of intuitionistic fuzzy set and respectively intuitionistic fuzzy logic).

Hidden Link Prediction in Stochastic Social Networks

Author : Pandey, Babita
Publisher : IGI Global
ISBN 13 : 1522590978
Total Pages : 281 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Hidden Link Prediction in Stochastic Social Networks by : Pandey, Babita

Download or read book Hidden Link Prediction in Stochastic Social Networks written by Pandey, Babita and published by IGI Global. This book was released on 2019-05-03 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: Link prediction is required to understand the evolutionary theory of computing for different social networks. However, the stochastic growth of the social network leads to various challenges in identifying hidden links, such as representation of graph, distinction between spurious and missing links, selection of link prediction techniques comprised of network features, and identification of network types. Hidden Link Prediction in Stochastic Social Networks concentrates on the foremost techniques of hidden link predictions in stochastic social networks including methods and approaches that involve similarity index techniques, matrix factorization, reinforcement, models, and graph representations and community detections. The book also includes miscellaneous methods of different modalities in deep learning, agent-driven AI techniques, and automata-driven systems and will improve the understanding and development of automated machine learning systems for supervised, unsupervised, and recommendation-driven learning systems. It is intended for use by data scientists, technology developers, professionals, students, and researchers.

Neutrosophic Sets and Systems, vol. 51/2022

Author : Florentin Smarandache
Publisher : Infinite Study
ISBN 13 :
Total Pages : 970 pages
Book Rating : 4./5 ( download)

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Book Synopsis Neutrosophic Sets and Systems, vol. 51/2022 by : Florentin Smarandache

Download or read book Neutrosophic Sets and Systems, vol. 51/2022 written by Florentin Smarandache and published by Infinite Study. This book was released on 2022-09-01 with total page 970 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Neutrosophic Sets and Systems” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc. Neutrosophy is a new branch of philosophy that studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. This theory considers every notion or idea together with its opposite or negation and with their spectrum of neutralities in between them (i.e. notions or ideas supporting neither nor ). The and ideas together are referred to as . Neutrosophy is a generalization of Hegel's dialectics (the last one is based on and only). According to this theory every idea tends to be neutralized and balanced by and ideas - as a state of equilibrium. In a classical way , , are disjoint two by two. But, since in many cases the borders between notions are vague, imprecise, Sorites, it is possible that , , (and of course) have common parts two by two, or even all three of them as well. Neutrosophic Set and Neutrosophic Logic are generalizations of the fuzzy set and respectively fuzzy logic (especially of intuitionistic fuzzy set and respectively intuitionistic fuzzy logic).

Handbook of Research on the Applications of Neutrosophic Sets Theory and Their Extensions in Education

Author : Broumi, Said
Publisher : IGI Global
ISBN 13 : 1668478374
Total Pages : 386 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Handbook of Research on the Applications of Neutrosophic Sets Theory and Their Extensions in Education by : Broumi, Said

Download or read book Handbook of Research on the Applications of Neutrosophic Sets Theory and Their Extensions in Education written by Broumi, Said and published by IGI Global. This book was released on 2023-06-09 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy sets have experienced multiple expansions since their conception to enhance their capacity to convey complex information. Intuitionistic fuzzy sets, image fuzzy sets, q-rung orthopair fuzzy sets, and neutrosophic sets are a few of these extensions. Researchers and academics have acquired a lot of information about their theories and methods for making decisions. However, only a small number of research findings discuss how neutrosophic sets theory and their extensions (NSTEs) are used in education. The Handbook of Research on the Applications of Neutrosophic Sets Theory and Their Extensions in Education implements fresh scientific approaches to enhance the quality of decisions under neutrosophic environments, particularly within education. Covering key topics such as data modeling, educational technologies, decision making, and learning management systems, this major reference work is ideal for instructional designers, researchers, academicians, scholars, practitioners, instructors, and students.

Neutrosophic Sets and Systems, Vol. 46, 2021

Author : Florentin Smarandache
Publisher : Infinite Study
ISBN 13 :
Total Pages : 487 pages
Book Rating : 4./5 ( download)

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Book Synopsis Neutrosophic Sets and Systems, Vol. 46, 2021 by : Florentin Smarandache

Download or read book Neutrosophic Sets and Systems, Vol. 46, 2021 written by Florentin Smarandache and published by Infinite Study. This book was released on 2021-10-19 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: Papers on neutrosophic programming, neutrosophic hypersoft set, neutrosophic topological spaces, NeutroAlgebra, NeutroGeometry, AntiGeometry, NeutroNearRings, neutrosophic differential equations, etc.

Optimization Theory Based on Neutrosophic and Plithogenic Sets

Author : Florentin Smarandache
Publisher : Academic Press
ISBN 13 : 0128199083
Total Pages : 448 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Optimization Theory Based on Neutrosophic and Plithogenic Sets by : Florentin Smarandache

Download or read book Optimization Theory Based on Neutrosophic and Plithogenic Sets written by Florentin Smarandache and published by Academic Press. This book was released on 2020-01-14 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization Theory Based on Neutrosophic and Plithogenic Sets presents the state-of-the-art research on neutrosophic and plithogenic theories and their applications in various optimization fields. Its table of contents covers new concepts, methods, algorithms, modelling, and applications of green supply chain, inventory control problems, assignment problems, transportation problem, nonlinear problems and new information related to optimization for the topic from the theoretical and applied viewpoints in neutrosophic sets and logic. All essential topics about neutrosophic optimization and Plithogenic sets make this volume the only single source of comprehensive information New and innovative theories help researchers solve problems under diverse optimization environments Varied applications address practitioner fields such as computational intelligence, image processing, medical diagnosis, fault diagnosis, and optimization design

HOW TO USE ANN FOR LINK PREDICTION IN SOCIAL NETWORK

Author : sneha soni
Publisher : Blue Rose Publishers
ISBN 13 :
Total Pages : 50 pages
Book Rating : 4./5 ( download)

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Book Synopsis HOW TO USE ANN FOR LINK PREDICTION IN SOCIAL NETWORK by : sneha soni

Download or read book HOW TO USE ANN FOR LINK PREDICTION IN SOCIAL NETWORK written by sneha soni and published by Blue Rose Publishers. This book was released on 2022-07-25 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social Networks (SNs) have attracted many users and have become an integrated part of the individual’s daily practices. The rapid climb of SNs like Twitter and Facebook has generated a great deal of knowledge that sets direction for research in social relationships. The knowledge network represented by Facebook is predicated on information transmission, sharing, and exchange. The prediction process from prior information of the event helps to know the evolution of social networks and assists the companies in effective decision making during a typical recommendation system . Social network connection prediction is an efficient technique for the analysis of the evolution of social organizations and formation of the social network relations.Link prediction is a crucial research direction within the field of complex networks and data processing . Some complex physical processes like local stochastic processes also are wont to measure the similarity between network nodes and improve the accuracy of the link prediction . In other words two linked nodes during a network may have a possible relationship. Analyzing whether there's a possible relationship can help to seek out potential links and tightness measures the intensity of the connection. Currently with the rapid development, online social networks have been a neighborhood of people’s life.

Graph Theoretic Approaches for Analyzing Large-Scale Social Networks

Author : Meghanathan, Natarajan
Publisher : IGI Global
ISBN 13 : 1522528156
Total Pages : 376 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Graph Theoretic Approaches for Analyzing Large-Scale Social Networks by : Meghanathan, Natarajan

Download or read book Graph Theoretic Approaches for Analyzing Large-Scale Social Networks written by Meghanathan, Natarajan and published by IGI Global. This book was released on 2017-07-13 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social network analysis has created novel opportunities within the field of data science. The complexity of these networks requires new techniques to optimize the extraction of useful information. Graph Theoretic Approaches for Analyzing Large-Scale Social Networks is a pivotal reference source for the latest academic research on emerging algorithms and methods for the analysis of social networks. Highlighting a range of pertinent topics such as influence maximization, probabilistic exploration, and distributed memory, this book is ideally designed for academics, graduate students, professionals, and practitioners actively involved in the field of data science.

Trends in Social Network Analysis

Author : Rokia Missaoui
Publisher : Springer
ISBN 13 : 3319534203
Total Pages : 263 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Trends in Social Network Analysis by : Rokia Missaoui

Download or read book Trends in Social Network Analysis written by Rokia Missaoui and published by Springer. This book was released on 2017-04-29 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking. It covers both new topics and new solutions to known problems. The contributions rely on established methods and techniques in graph theory, machine learning, stochastic modelling, user behavior analysis and natural language processing, just to name a few. This text provides an understanding of using such methods and techniques in order to manage practical problems and situations. Trends in Social Network Analysis: Information Propagation, User Behavior Modelling, Forecasting, and Vulnerability Assessment appeals to students, researchers, and professionals working in the field.

Prediction and Inference from Social Networks and Social Media

Author : Jalal Kawash
Publisher : Springer
ISBN 13 : 3319510495
Total Pages : 231 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Prediction and Inference from Social Networks and Social Media by : Jalal Kawash

Download or read book Prediction and Inference from Social Networks and Social Media written by Jalal Kawash and published by Springer. This book was released on 2017-03-16 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the challenges of social network and social media analysis in terms of prediction and inference. The chapters collected here tackle these issues by proposing new analysis methods and by examining mining methods for the vast amount of social content produced. Social Networks (SNs) have become an integral part of our lives; they are used for leisure, business, government, medical, educational purposes and have attracted billions of users. The challenges that stem from this wide adoption of SNs are vast. These include generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, and behavior detection. This text has applications to widely used platforms such as Twitter and Facebook and appeals to students, researchers, and professionals in the field.

Social Networks with Rich Edge Semantics

Author : Quan Zheng
Publisher : CRC Press
ISBN 13 : 1315390612
Total Pages : 210 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Social Networks with Rich Edge Semantics by : Quan Zheng

Download or read book Social Networks with Rich Edge Semantics written by Quan Zheng and published by CRC Press. This book was released on 2017-08-15 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social Networks with Rich Edge Semantics introduces a new mechanism for representing social networks in which pairwise relationships can be drawn from a range of realistic possibilities, including different types of relationships, different strengths in the directions of a pair, positive and negative relationships, and relationships whose intensities change with time. For each possibility, the book shows how to model the social network using spectral embedding. It also shows how to compose the techniques so that multiple edge semantics can be modeled together, and the modeling techniques are then applied to a range of datasets. Features Introduces the reader to difficulties with current social network analysis, and the need for richer representations of relationships among nodes, including accounting for intensity, direction, type, positive/negative, and changing intensities over time Presents a novel mechanism to allow social networks with qualitatively different kinds of relationships to be described and analyzed Includes extensions to the important technique of spectral embedding, shows that they are mathematically well motivated and proves that their results are appropriate Shows how to exploit embeddings to understand structures within social networks, including subgroups, positional significance, link or edge prediction, consistency of role in different contexts, and net flow of properties through a node Illustrates the use of the approach for real-world problems for online social networks, criminal and drug smuggling networks, and networks where the nodes are themselves groups Suitable for researchers and students in social network research, data science, statistical learning, and related areas, this book will help to provide a deeper understanding of real-world social networks.

Machine Learning in Social Networks

Author : Manasvi Aggarwal
Publisher : Springer Nature
ISBN 13 : 9813340223
Total Pages : 121 pages
Book Rating : 4.8/5 (133 download)

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Book Synopsis Machine Learning in Social Networks by : Manasvi Aggarwal

Download or read book Machine Learning in Social Networks written by Manasvi Aggarwal and published by Springer Nature. This book was released on 2020-11-25 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with network representation learning. It deals with embedding nodes, edges, subgraphs and graphs. There is a growing interest in understanding complex systems in different domains including health, education, agriculture and transportation. Such complex systems are analyzed by modeling, using networks that are aptly called complex networks. Networks are becoming ubiquitous as they can represent many real-world relational data, for instance, information networks, molecular structures, telecommunication networks and protein–protein interaction networks. Analysis of these networks provides advantages in many fields such as recommendation (recommending friends in a social network), biological field (deducing connections between proteins for treating new diseases) and community detection (grouping users of a social network according to their interests) by leveraging the latent information of networks. An active and important area of current interest is to come out with algorithms that learn features by embedding nodes or (sub)graphs into a vector space. These tasks come under the broad umbrella of representation learning. A representation learning model learns a mapping function that transforms the graphs' structure information to a low-/high-dimension vector space maintaining all the relevant properties.