Individual And Collective Graph Mining
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Individual And Collective Graph Mining
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Author : Danai Koutra
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Individual And Collective Graph Mining written by Danai Koutra and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
Graphs naturally represent information ranging from links between web pages, to communication in email networks, to connections between neurons in our brains. These graphs often span billions of nodes and interactions between them. Within this deluge of interconnected data, how can we find the most important structures and summarize them? How can we efficiently visualize them? How can we detect anomalies that indicate critical events, such as an attack on a computer system, disease formation in the human brain, or the fall of a company? This book presents scalable, principled discovery algorithms that combine globality with locality to make sense of one or more graphs. In addition to fast algorithmic methodologies, we also contribute graph-theoretical ideas and models, and real-world applications in two main areas: Individual Graph Mining: We show how to interpretably summarize a single graph by identifying its important graph structures. We complement summarization with inference, which leverages information about few entities (obtained via summarization or other methods) and the network structure to efficiently and effectively learn information about the unknown entities. Collective Graph Mining: We extend the idea of individual-graph summarization to time-evolving graphs, and show how to scalably discover temporal patterns. Apart from summarization, we claim that graph similarity is often the underlying problem in a host of applications where multiple graphs occur (e.g., temporal anomaly detection, discovery of behavioral patterns), and we present principled, scalable algorithms for aligning networks and measuring their similarity. The methods that we present in this book leverage techniques from diverse areas, such as matrix algebra, graph theory, optimization, information theory, machine learning, finance, and social science,to solve real-world problems. We present applications of our exploration algorithms to massive datasets, including a Web graph of 6.6 billion edges, a Twitter graph of 1.8 billion edges, brain graphs with up to 90 million edges, collaboration, peer-to-peer networks, browser logs, all spanning millions of users and interactions.
Exploiting The Power Of Group Differences
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Author : Guozhu Dong
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Exploiting The Power Of Group Differences written by Guozhu Dong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
This book presents pattern-based problem-solving methods for a variety of machine learning and data analysis problems. The methods are all based on techniques that exploit the power of group differences. They make use of group differences represented using emerging patterns (aka contrast patterns), which are patterns that match significantly different numbers of instances in different data groups. A large number of applications outside of the computing discipline are also included. Emerging patterns (EPs) are useful in many ways. EPs can be used as features, as simple classifiers, as subpopulation signatures/characterizations, and as triggering conditions for alerts. EPs can be used in gene ranking for complex diseases since they capture multi-factor interactions. The length of EPs can be used to detect anomalies, outliers, and novelties. Emerging/contrast pattern based methods for clustering analysis and outlier detection do not need distance metrics, avoiding pitfalls of the latter in exploratory analysis of high dimensional data. EP-based classifiers can achieve good accuracy even when the training datasets are tiny, making them useful for exploratory compound selection in drug design. EPs can serve as opportunities in opportunity-focused boosting and are useful for constructing powerful conditional ensembles. EP-based methods often produce interpretable models and results. In general, EPs are useful for classification, clustering, outlier detection, gene ranking for complex diseases, prediction model analysis and improvement, and so on. EPs are useful for many tasks because they represent group differences, which have extraordinary power. Moreover, EPs represent multi-factor interactions, whose effective handling is of vital importance and is a major challenge in many disciplines. Based on the results presented in this book, one can clearly say that patterns are useful, especially when they are linked to issues of interest. We believe that many effective ways to exploit group differences' power still remain to be discovered. Hopefully this book will inspire readers to discover such new ways, besides showing them existing ways, to solve various challenging problems.
Querying Graphs
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Author : Angela Bonifati
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2018-10-01
Querying Graphs written by Angela Bonifati and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-01 with Computers categories.
Graph data modeling and querying arises in many practical application domains such as social and biological networks where the primary focus is on concepts and their relationships and the rich patterns in these complex webs of interconnectivity. In this book, we present a concise unified view on the basic challenges which arise over the complete life cycle of formulating and processing queries on graph databases. To that purpose, we present all major concepts relevant to this life cycle, formulated in terms of a common and unifying ground: the property graph data model—the pre-dominant data model adopted by modern graph database systems. We aim especially to give a coherent and in-depth perspective on current graph querying and an outlook for future developments. Our presentation is self-contained, covering the relevant topics from: graph data models, graph query languages and graph query specification, graph constraints, and graph query processing. We conclude by indicating major open research challenges towards the next generation of graph data management systems.
Tenth International Conference On Applications And Techniques In Cyber Intelligence Icatci 2022
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Author : Jemal H. Abawajy
language : en
Publisher: Springer Nature
Release Date : 2023-03-29
Tenth International Conference On Applications And Techniques In Cyber Intelligence Icatci 2022 written by Jemal H. Abawajy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-29 with Computers categories.
This book presents innovative ideas, cutting-edge findings, and novel techniques, methods, and applications in a broad range of cybersecurity and cyberthreat intelligence areas. As our society becomes smarter, there is a corresponding need to secure our cyberfuture. The book describes approaches and findings that are of interest to business professionals and governments seeking to secure our data and underpin infrastructures, as well as to individual users.
Correlation Clustering
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Author : Francesco Bonchi
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2022-03-08
Correlation Clustering written by Francesco Bonchi and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-08 with Computers categories.
Given a set of objects and a pairwise similarity measure between them, the goal of correlation clustering is to partition the objects in a set of clusters to maximize the similarity of the objects within the same cluster and minimize the similarity of the objects in different clusters. In most of the variants of correlation clustering, the number of clusters is not a given parameter; instead, the optimal number of clusters is automatically determined. Correlation clustering is perhaps the most natural formulation of clustering: as it just needs a definition of similarity, its broad generality makes it applicable to a wide range of problems in different contexts, and, particularly, makes it naturally suitable to clustering structured objects for which feature vectors can be difficult to obtain. Despite its simplicity, generality, and wide applicability, correlation clustering has so far received much more attention from an algorithmic-theory perspective than from the data-mining community. The goal of this lecture is to show how correlation clustering can be a powerful addition to the toolkit of a data-mining researcher and practitioner, and to encourage further research in the area.
Detecting Fake News On Social Media
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Author : Kai Shu
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Detecting Fake News On Social Media written by Kai Shu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
In the past decade, social media has become increasingly popular for news consumption due to its easy access, fast dissemination, and low cost. However, social media also enables the wide propagation of "fake news," i.e., news with intentionally false information. Fake news on social media can have significant negative societal effects. Therefore, fake news detection on social media has recently become an emerging research area that is attracting tremendous attention. This book, from a data mining perspective, introduces the basic concepts and characteristics of fake news across disciplines, reviews representative fake news detection methods in a principled way, and illustrates challenging issues of fake news detection on social media. In particular, we discussed the value of news content and social context, and important extensions to handle early detection, weakly-supervised detection, and explainable detection. The concepts, algorithms, and methods described in this lecture can help harness the power of social media to build effective and intelligent fake news detection systems. This book is an accessible introduction to the study of detecting fake news on social media. It is an essential reading for students, researchers, and practitioners to understand, manage, and excel in this area. This book is supported by additional materials, including lecture slides, the complete set of figures, key references, datasets, tools used in this book, and the source code of representative algorithms. The readers are encouraged to visit the book website for the latest information: http://dmml.asu.edu/dfn/
Databases Theory And Applications
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Author : Hua Wang
language : en
Publisher: Springer
Release Date : 2014-07-04
Databases Theory And Applications written by Hua Wang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-04 with Computers categories.
This book constitutes the refereed proceedings of the 25th Australasian Database Conference, ADC 2014, held in Brisbane, NSW, Australia, in July 2014. The 15 full papers presented together with 6 short papers and 2 keynotes were carefully reviewed and selected from 38 submissions. A large variety of subjects are covered, including hot topics such as data warehousing; database integration; mobile databases; cloud, distributed, and parallel databases; high dimensional and temporal data; image/video retrieval and databases; database performance and tuning; privacy and security in databases; query processing and optimization; semi-structured data and XML; spatial data processing and management; stream and sensor data management; uncertain and probabilistic databases; web databases; graph databases; web service management; and social media data management.
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Author :
language : en
Publisher: IOS Press
Release Date :
written by and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Graph Theoretic Approaches For Analyzing Large Scale Social Networks
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Author : Meghanathan, Natarajan
language : en
Publisher: IGI Global
Release Date : 2017-07-13
Graph Theoretic Approaches For Analyzing Large Scale Social Networks written by Meghanathan, Natarajan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-13 with Computers categories.
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.
Databases Theory And Applications
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Author : Zhifeng Bao
language : en
Publisher: Springer Nature
Release Date : 2023-11-06
Databases Theory And Applications written by Zhifeng Bao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-06 with Computers categories.
This book constitutes the refereed proceedings of the 34th Australasian Database Conference on Databases Theory and Applications, ADC 2023, held in Melbourne, VIC, Australia, during November 1-3, 2023. The 26 full papers presented in this volume are carefully reviewed and selected from 41 submissions. They were organized in topical sections named: Mining Complex Types of Data, Natural Language Processing and Text Analysis, Machine Learning and Computer Vision, Database Systems and Data Storage, Data Quality and Fairness for Graphs and Graph Mining and Graph Algorithms.