Author : Stefano Leonardi
Publisher :
Page : 798 pages
File Size : 46,70 MB
Release : 2013
Category : Computer science
ISBN : 9781450318693
Author : Xueqi Cheng
Publisher :
Page : 466 pages
File Size : 21,11 MB
Release : 2015
Category : Computer science
ISBN : 9781450333177
Author : B. Thuraisingham
Publisher : Springer
Page : 382 pages
File Size : 22,14 MB
Release : 2005-12-15
Category : Computers
ISBN : 030647008X
New technology is always evolving and companies must have appropriate security for their businesses to be able to keep up to date with the changes. With the rapid growth of the internet and the world wide web, data and applications security will always be a key topic in industry as well as in the public sector, and has implications for the whole of society. Data and Applications Security covers issues related to security and privacy of information in a wide range of applications, including: Electronic Commerce, XML and Web Security; Workflow Security and Role-based Access Control; Distributed Objects and Component Security; Inference Problem, Data Mining and Intrusion Detection; Language and SQL Security; Security Architectures and Frameworks; Federated and Distributed Systems Security; Encryption, Authentication and Security Policies. This book contains papers and panel discussions from the Fourteenth Annual Working Conference on Database Security, which is part of the Database Security: Status and Prospects conference series sponsored by the International Federation for Information Processing (IFIP). The conference was held in Schoorl, The Netherlands in August 2000.
Author : Hillol Kargupta
Publisher : SIAM
Page : 670 pages
File Size : 46,35 MB
Release : 2005-04-01
Category : Mathematics
ISBN : 9780898715934
The Fifth SIAM International Conference on Data Mining continues the tradition of providing an open forum for the presentation and discussion of innovative algorithms as well as novel applications of data mining. Advances in information technology and data collection methods have led to the availability of large data sets in commercial enterprises and in a wide variety of scientific and engineering disciplines. The field of data mining draws upon extensive work in areas such as statistics, machine learning, pattern recognition, databases, and high performance computing to discover interesting and previously unknown information in data. This conference results in data mining, including applications, algorithms, software, and systems.
Author : Deepayan Chakrabarti
Publisher : Morgan & Claypool Publishers
Page : 209 pages
File Size : 43,71 MB
Release : 2012-10-01
Category : Computers
ISBN : 160845116X
What does the Web look like? How can we find patterns, communities, outliers, in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings, for example in social networks, computer-communication networks (intrusion detection, traffic management), protein-protein interaction networks in biology, document-text bipartite graphs in text retrieval, person-account graphs in financial fraud detection, and others. In this work, first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are important, because they can help with "what if" scenarios, extrapolations, and anonymization. Then we provide a list of powerful tools for graph analysis, and specifically spectral methods (Singular Value Decomposition (SVD)), tensors, and case studies like the famous "pageRank" algorithm and the "HITS" algorithm for ranking web search results. Finally, we conclude with a survey of tools and observations from related fields like sociology, which provide complementary viewpoints. Table of Contents: Introduction / Patterns in Static Graphs / Patterns in Evolving Graphs / Patterns in Weighted Graphs / Discussion: The Structure of Specific Graphs / Discussion: Power Laws and Deviations / Summary of Patterns / Graph Generators / Preferential Attachment and Variants / Incorporating Geographical Information / The RMat / Graph Generation by Kronecker Multiplication / Summary and Practitioner's Guide / SVD, Random Walks, and Tensors / Tensors / Community Detection / Influence/Virus Propagation and Immunization / Case Studies / Social Networks / Other Related Work / Conclusions
Author : David C. Wyld
Publisher : Springer Science & Business Media
Page : 677 pages
File Size : 50,34 MB
Release : 2011-06-30
Category : Computers
ISBN : 364222539X
This book constitutes the proceedings of the 4th International Conference on Network Security and Applications held in Chennai, India, in July 2011. The 63 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers address all technical and practical aspects of security and its applications for wired and wireless networks and are organized in topical sections on network security and applications, ad hoc, sensor and ubiquitous computing, as well as peer-to-peer networks and trust management.
Author : Brij Masand
Publisher : Springer Science & Business Media
Page : 190 pages
File Size : 12,70 MB
Release : 2000-07-26
Category : Computers
ISBN : 3540678182
After the advent of data mining and its successful application on conventional data, Web-related information has been an appropriate and increasingly popular target of knowledge discovery. Depending on whether the data used in the knowledge discovery process concerns the Web itself in terms of content or the usage of the content, one distinguishes between Web content mining and Web usage mining. This book is the first one entirely devoted to Web usage mining. It originates from the WEBKDD'99 Workshop held during the 1999 KDD Conference. The ten revised full papers presented together with an introductory survey by the volume editors documents the state of the art in this exciting new area. The book presents topical sections on Modeling the User, Discovering Rules and Patterns of Navigation, and Measuring interestingness in Web Usage Mining.
Author : Charu C. Aggarwal
Publisher : Springer Science & Business Media
Page : 508 pages
File Size : 46,68 MB
Release : 2011-03-18
Category : Computers
ISBN : 1441984623
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.
Author : Bin Li
Publisher : CRC Press
Page : 227 pages
File Size : 19,36 MB
Release : 2018-10-30
Category : Business & Economics
ISBN : 1482249642
With the aim to sequentially determine optimal allocations across a set of assets, Online Portfolio Selection (OLPS) has significantly reshaped the financial investment landscape. Online Portfolio Selection: Principles and Algorithms supplies a comprehensive survey of existing OLPS principles and presents a collection of innovative strategies that leverage machine learning techniques for financial investment. The book presents four new algorithms based on machine learning techniques that were designed by the authors, as well as a new back-test system they developed for evaluating trading strategy effectiveness. The book uses simulations with real market data to illustrate the trading strategies in action and to provide readers with the confidence to deploy the strategies themselves. The book is presented in five sections that: Introduce OLPS and formulate OLPS as a sequential decision task Present key OLPS principles, including benchmarks, follow the winner, follow the loser, pattern matching, and meta-learning Detail four innovative OLPS algorithms based on cutting-edge machine learning techniques Provide a toolbox for evaluating the OLPS algorithms and present empirical studies comparing the proposed algorithms with the state of the art Investigate possible future directions Complete with a back-test system that uses historical data to evaluate the performance of trading strategies, as well as MATLAB® code for the back-test systems, this book is an ideal resource for graduate students in finance, computer science, and statistics. It is also suitable for researchers and engineers interested in computational investment. Readers are encouraged to visit the authors’ website for updates: http://olps.stevenhoi.org.
Author : Joydeep Ghosh
Publisher : SIAM
Page : 662 pages
File Size : 50,80 MB
Release : 2006-04-01
Category : Computers
ISBN : 9780898716115
The Sixth SIAM International Conference on Data Mining continues the tradition of presenting approaches, tools, and systems for data mining in fields such as science, engineering, industrial processes, healthcare, and medicine. The datasets in these fields are large, complex, and often noisy. Extracting knowledge requires the use of sophisticated, high-performance, and principled analysis techniques and algorithms, based on sound statistical foundations. These techniques in turn require powerful visualization technologies; implementations that must be carefully tuned for performance; software systems that are usable by scientists, engineers, and physicians as well as researchers; and infrastructures that support them.
