Community Search Over Big Graphs

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Community Search over Big Graphs

Author : Xin Huang
Publisher : Springer Nature
ISBN 13 : 3031018745
Total Pages : 188 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Community Search over Big Graphs by : Xin Huang

Download or read book Community Search over Big Graphs written by Xin Huang and published by Springer Nature. This book was released on 2022-05-31 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Communities serve as basic structural building blocks for understanding the organization of many real-world networks, including social, biological, collaboration, and communication networks. Recently, community search over graphs has attracted significantly increasing attention, from small, simple, and static graphs to big, evolving, attributed, and location-based graphs. In this book, we first review the basic concepts of networks, communities, and various kinds of dense subgraph models. We then survey the state of the art in community search techniques on various kinds of networks across different application areas. Specifically, we discuss cohesive community search, attributed community search, social circle discovery, and geo-social group search. We highlight the challenges posed by different community search problems. We present their motivations, principles, methodologies, algorithms, and applications, and provide a comprehensive comparison of the existing techniques. This book finally concludes by listing publicly available real-world datasets and useful tools for facilitating further research, and by offering further readings and future directions of research in this important and growing area.

Community Search Over Big Graphs

Author : Xin Huang
Publisher : Morgan & Claypool
ISBN 13 : 9781681735955
Total Pages : 206 pages
Book Rating : 4.7/5 (359 download)

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Book Synopsis Community Search Over Big Graphs by : Xin Huang

Download or read book Community Search Over Big Graphs written by Xin Huang and published by Morgan & Claypool. This book was released on 2019-08-07 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Communities serve as basic structural building blocks for understanding the organization of many real-world networks, including social, biological, collaboration, and communication networks. Recently, community search over graphs has attracted significantly increasing attention, from small, simple, and static graphs to big, evolving, attributed, and location-based graphs. In this book, we first review the basic concepts of networks, communities, and various kinds of dense subgraph models. We then survey the state of the art in community search techniques on various kinds of networks across different application areas. Specifically, we discuss cohesive community search, attributed community search, social circle discovery, and geo-social group search. We highlight the challenges posed by different community search problems. We present their motivations, principles, methodologies, algorithms, and applications, and provide a comprehensive comparison of the existing techniques. This book finally concludes by listing publicly available real-world datasets and useful tools for facilitating further research, and by offering further readings and future directions of research in this important and growing area.

Social Networks and Questions of Big Data. Graph search for communities with corresponding keywords

Author : Andrea Attwenger
Publisher : GRIN Verlag
ISBN 13 : 3668471754
Total Pages : 11 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Social Networks and Questions of Big Data. Graph search for communities with corresponding keywords by : Andrea Attwenger

Download or read book Social Networks and Questions of Big Data. Graph search for communities with corresponding keywords written by Andrea Attwenger and published by GRIN Verlag. This book was released on 2017-06-27 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seminar paper from the year 2017 in the subject Computer Science - Internet, New Technologies, grade: 1.3, LMU Munich (Institut für Informatik), course: Recent Developments in Data Science, language: English, abstract: This essay deals with a graph search for communities with corresponding keywords. The era of big data and world-spanning social networks has highlighted the necessity of ways to make sense of this vast amount of information. Data can be arranged in a graph of connected vertices, therefore giving it a basic structure. If the vertices are further described by keywords, the structure is called an attributed graph. This paper discusses a query algorithm that scans these attributed graphs for communities that are not only structurally linked - therefore forming subgraphs - but also share the same keywords. This method might give new insights into the composition of large networks, highlight interesting connections and give opportunities for effectively targeted marketing. As a specific use case, the idea of the attributed community query is applied to the example of a film recommendation program.

Cohesive Subgraph Search Over Large Heterogeneous Information Networks

Author : Yixiang Fang
Publisher : Springer Nature
ISBN 13 : 3030975681
Total Pages : 86 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Cohesive Subgraph Search Over Large Heterogeneous Information Networks by : Yixiang Fang

Download or read book Cohesive Subgraph Search Over Large Heterogeneous Information Networks written by Yixiang Fang and published by Springer Nature. This book was released on 2022-05-06 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: This SpringerBrief provides the first systematic review of the existing works of cohesive subgraph search (CSS) over large heterogeneous information networks (HINs). It also covers the research breakthroughs of this area, including models, algorithms and comparison studies in recent years. This SpringerBrief offers a list of promising future research directions of performing CSS over large HINs. The authors first classify the existing works of CSS over HINs according to the classic cohesiveness metrics such as core, truss, clique, connectivity, density, etc., and then extensively review the specific models and their corresponding search solutions in each group. Note that since the bipartite network is a special case of HINs, all the models developed for general HINs can be directly applied to bipartite networks, but the models customized for bipartite networks may not be easily extended for other general HINs due to their restricted settings. The authors also analyze and compare these cohesive subgraph models (CSMs) and solutions systematically. Specifically, the authors compare different groups of CSMs and analyze both their similarities and differences, from multiple perspectives such as cohesiveness constraints, shared properties, and computational efficiency. Then, for the CSMs in each group, the authors further analyze and compare their model properties and high-level algorithm ideas. This SpringerBrief targets researchers, professors, engineers and graduate students, who are working in the areas of graph data management and graph mining. Undergraduate students who are majoring in computer science, databases, data and knowledge engineering, and data science will also want to read this SpringerBrief.

On Uncertain Graphs

Author : Arijit Khan
Publisher : Springer Nature
ISBN 13 : 3031018605
Total Pages : 80 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis On Uncertain Graphs by : Arijit Khan

Download or read book On Uncertain Graphs written by Arijit Khan and published by Springer Nature. This book was released on 2022-05-31 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measurements, lack of precise information needs, inference and prediction models, or explicit manipulation, e.g., for privacy purposes. Therefore, uncertain, or probabilistic, graphs are increasingly used to represent noisy linked data in many emerging application scenarios, and they have recently become a hot topic in the database and data mining communities. Many classical algorithms such as reachability and shortest path queries become #P-complete and, thus, more expensive over uncertain graphs. Moreover, various complex queries and analytics are also emerging over uncertain networks, such as pattern matching, information diffusion, and influence maximization queries. In this book, we discuss the sources of uncertain graphs and their applications, uncertainty modeling, as well as the complexities and algorithmic advances on uncertain graphs processing in the context of both classical and emerging graph queries and analytics. We emphasize the current challenges and highlight some future research directions.

ECAI 2023

Author : K. Gal
Publisher : IOS Press
ISBN 13 : 164368437X
Total Pages : 3328 pages
Book Rating : 4.6/5 (436 download)

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Book Synopsis ECAI 2023 by : K. Gal

Download or read book ECAI 2023 written by K. Gal and published by IOS Press. This book was released on 2023-10-18 with total page 3328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrate innovative applications and uses of advanced AI technology. ECAI 2023 received 1896 submissions – a record number – of which 1691 were retained for review, ultimately resulting in an acceptance rate of 23%. The 390 papers included here, cover topics including machine learning, natural language processing, multi agent systems, and vision and knowledge representation and reasoning. PAIS 2023 received 17 submissions, of which 10 were accepted after a rigorous review process. Those 10 papers cover topics ranging from fostering better working environments, behavior modeling and citizen science to large language models and neuro-symbolic applications, and are also included here. Presenting a comprehensive overview of current research and developments in AI, the book will be of interest to all those working in the field.

Overlapping Community Search in Very Large Graphs

Author : Arnau Padrol Sureda
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (85 download)

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Book Synopsis Overlapping Community Search in Very Large Graphs by : Arnau Padrol Sureda

Download or read book Overlapping Community Search in Very Large Graphs written by Arnau Padrol Sureda and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this master thesis we present a novel approach to finding communities in large graphs. Our method finds the overlapped and hierarchical structure of communities efficiently, outperforming previous proposals. We propose a new objective function that allows to evaluate the quality of a community naturally including nodes shared by other communities. This is achieved by implicitly mapping the nodes of the graph in a vectorial space, using as a basis a construction presented by Lóvasz in 1979. We present and analyse several algorithms to decompose a given graph into a set of not necessarily disjoint neighborhoods. This has applications for analysing and summarizing the large-scale structure of complex networks.

Web and Big Data

Author : Xin Wang
Publisher : Springer Nature
ISBN 13 : 3030602591
Total Pages : 829 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Web and Big Data by : Xin Wang

Download or read book Web and Big Data written by Xin Wang and published by Springer Nature. This book was released on 2020-10-15 with total page 829 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set, LNCS 11317 and 12318, constitutes the thoroughly refereed proceedings of the 4th International Joint Conference, APWeb-WAIM 2020, held in Tianjin, China, in September 2020. Due to the COVID-19 pandemic the conference was organizedas a fully online conference. The 42 full papers presented together with 17 short papers, and 6 demonstration papers were carefully reviewed and selected from 180 submissions. The papers are organized around the following topics: Big Data Analytics; Graph Data and Social Networks; Knowledge Graph; Recommender Systems; Information Extraction and Retrieval; Machine Learning; Blockchain; Data Mining; Text Analysis and Mining; Spatial, Temporal and Multimedia Databases; Database Systems; and Demo.

Database Systems for Advanced Applications

Author : Arnab Bhattacharya
Publisher : Springer Nature
ISBN 13 : 3031001230
Total Pages : 788 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Database Systems for Advanced Applications by : Arnab Bhattacharya

Download or read book Database Systems for Advanced Applications written by Arnab Bhattacharya and published by Springer Nature. This book was released on 2022-04-26 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 13245, 13246 and 13247 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held online, in April 2021. The total of 72 full papers, along with 76 short papers, are presented in this three-volume set was carefully reviewed and selected from 543 submissions. Additionally, 13 industrial papers, 9 demo papers and 2 PhD consortium papers are included. The conference was planned to take place in Hyderabad, India, but it was held virtually due to the COVID-19 pandemic.

Graph Algorithms

Author : Mark Needham
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492047635
Total Pages : 297 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Graph Algorithms by : Mark Needham

Download or read book Graph Algorithms written by Mark Needham and published by "O'Reilly Media, Inc.". This book was released on 2019-05-16 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how graph algorithms can help you leverage the relationships within your data to develop more intelligent solutions and enhance your machine learning models. You’ll learn how graph analytics are uniquely suited to unfold complex structures and reveal difficult-to-find patterns lurking in your data. Whether you are trying to build dynamic network models or forecast real-world behavior, this book illustrates how graph algorithms deliver value—from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. This practical book walks you through hands-on examples of how to use graph algorithms in Apache Spark and Neo4j—two of the most common choices for graph analytics. Also included: sample code and tips for over 20 practical graph algorithms that cover optimal pathfinding, importance through centrality, and community detection. Learn how graph analytics vary from conventional statistical analysis Understand how classic graph algorithms work, and how they are applied Get guidance on which algorithms to use for different types of questions Explore algorithm examples with working code and sample datasets from Spark and Neo4j See how connected feature extraction can increase machine learning accuracy and precision Walk through creating an ML workflow for link prediction combining Neo4j and Spark

Database Systems for Advanced Applications

Author : Christian S. Jensen
Publisher : Springer Nature
ISBN 13 : 3030731944
Total Pages : 683 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Database Systems for Advanced Applications by : Christian S. Jensen

Download or read book Database Systems for Advanced Applications written by Christian S. Jensen and published by Springer Nature. This book was released on 2021-04-06 with total page 683 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 12681-12683 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, held in Taipei, Taiwan, in April 2021. The total of 156 papers presented in this three-volume set was carefully reviewed and selected from 490 submissions. The topic areas for the selected papers include information retrieval, search and recommendation techniques; RDF, knowledge graphs, semantic web, and knowledge management; and spatial, temporal, sequence, and streaming data management, while the dominant keywords are network, recommendation, graph, learning, and model. These topic areas and keywords shed the light on the direction where the research in DASFAA is moving towards. Due to the Corona pandemic this event was held virtually.

Database Systems for Advanced Applications

Author : Guoliang Li
Publisher : Springer
ISBN 13 : 3030185761
Total Pages : 829 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Database Systems for Advanced Applications by : Guoliang Li

Download or read book Database Systems for Advanced Applications written by Guoliang Li and published by Springer. This book was released on 2019-04-23 with total page 829 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 11446 and LNCS 11447 constitutes the refereed proceedings of the 24th International Conference on Database Systems for Advanced Applications, DASFAA 2019, held in Chiang Mai, Thailand, in April 2019. The 92 full papers and 64 short papers were carefully selected from a total of 501 submissions. In addition, 13 demo papers and 6 tutorial papers are included. The full papers are organized in the following topics: big data; clustering and classification; crowdsourcing; data integration; embedding; graphs; knowledge graph; machine learning; privacy and graph; recommendation; social network; spatial; and spatio-temporal. The short papers, demo papers, and tutorial papers can be found in the volume LNCS 11448, which also includes the workshops of DASFAA 2019.

Effective and Efficient Community Search Over Large Attributed Graphs

Author : 方一向
Publisher :
ISBN 13 :
Total Pages : 203 pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis Effective and Efficient Community Search Over Large Attributed Graphs by : 方一向

Download or read book Effective and Efficient Community Search Over Large Attributed Graphs written by 方一向 and published by . This book was released on 2017 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Spatial Data and Intelligence

Author : Xiaofeng Meng
Publisher : Springer Nature
ISBN 13 : 3031329104
Total Pages : 274 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Spatial Data and Intelligence by : Xiaofeng Meng

Download or read book Spatial Data and Intelligence written by Xiaofeng Meng and published by Springer Nature. This book was released on 2023-05-10 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Conference on Spatial Data and Intelligence, SpatialDI 2023, held in Nanchang, China, in April 13–15, 2023. The 18 full papers included in this book were carefully reviewed and selected from 68 submissions. They were organized in topical sections as follows: traffic management; visualization analysis; spatial big data analysis; spatiotemporal data mining; spatiotemporal data storage; and metaverse.

Storytelling with Data

Author : Cole Nussbaumer Knaflic
Publisher : John Wiley & Sons
ISBN 13 : 1119002265
Total Pages : 284 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Storytelling with Data by : Cole Nussbaumer Knaflic

Download or read book Storytelling with Data written by Cole Nussbaumer Knaflic and published by John Wiley & Sons. This book was released on 2015-10-09 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!

Computational Complexity

Author : Robert A. Meyers
Publisher : Springer
ISBN 13 : 9781461417996
Total Pages : 0 pages
Book Rating : 4.4/5 (179 download)

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Book Synopsis Computational Complexity by : Robert A. Meyers

Download or read book Computational Complexity written by Robert A. Meyers and published by Springer. This book was released on 2011-10-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex systems are systems that comprise many interacting parts with the ability to generate a new quality of collective behavior through self-organization, e.g. the spontaneous formation of temporal, spatial or functional structures. These systems are often characterized by extreme sensitivity to initial conditions as well as emergent behavior that are not readily predictable or even completely deterministic. The recognition that the collective behavior of the whole system cannot be simply inferred from an understanding of the behavior of the individual components has led to the development of numerous sophisticated new computational and modeling tools with applications to a wide range of scientific, engineering, and societal phenomena. Computational Complexity: Theory, Techniques and Applications presents a detailed and integrated view of the theoretical basis, computational methods, and state-of-the-art approaches to investigating and modeling of inherently difficult problems whose solution requires extensive resources approaching the practical limits of present-day computer systems. This comprehensive and authoritative reference examines key components of computational complexity, including cellular automata, graph theory, data mining, granular computing, soft computing, wavelets, and more.

Handbook of Graphs and Networks in People Analytics

Author : Keith McNulty
Publisher : CRC Press
ISBN 13 : 100059727X
Total Pages : 266 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Handbook of Graphs and Networks in People Analytics by : Keith McNulty

Download or read book Handbook of Graphs and Networks in People Analytics written by Keith McNulty and published by CRC Press. This book was released on 2022-06-19 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Graphs and Networks in People Analytics: With Examples in R and Python covers the theory and practical implementation of graph methods in R and Python for the analysis of people and organizational networks. Starting with an overview of the origins of graph theory and its current applications in the social sciences, the book proceeds to give in-depth technical instruction on how to construct and store graphs from data, how to visualize those graphs compellingly and how to convert common data structures into graph-friendly form. The book explores critical elements of network analysis in detail, including the measurement of distance and centrality, the detection of communities and cliques, and the analysis of assortativity and similarity. An extension chapter offers an introduction to graph database technologies. Real data sets from various research contexts are used for both instruction and for end of chapter practice exercises and a final chapter contains data sets and exercises ideal for larger personal or group projects of varying difficulty level. Key features: Immediately implementable code, with extensive and varied illustrations of graph variants and layouts. Examples and exercises across a variety of real-life contexts including business, politics, education, social media and crime investigation. Dedicated chapter on graph visualization methods. Practical walkthroughs of common methodological uses: finding influential actors in groups, discovering hidden community structures, facilitating diverse interaction in organizations, detecting political alignment, determining what influences connection and attachment. Various downloadable data sets for use both in class and individual learning projects. Final chapter dedicated to individual or group project examples.