Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Data Mining Fraud Detection And Mobile Telecommunications
Download Data Mining Fraud Detection And Mobile Telecommunications full books in PDF, epub, and Kindle. Read online Data Mining Fraud Detection And Mobile Telecommunications ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Data Mining, Fraud Detection and Mobile Telecommunications by : Olusola Adeniyi Abidogun
Download or read book Data Mining, Fraud Detection and Mobile Telecommunications written by Olusola Adeniyi Abidogun and published by . This book was released on 2005 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research investigated the unsupervised learning potentials of two neural networks (Self-Organizing Maps and Long Short-Term Memory) for the profiling of calls made by users over a period of time in a mobile telecommunication network.
Book Synopsis Encyclopedia of Organizational Knowledge, Administration, and Technology by : Khosrow-Pour D.B.A., Mehdi
Download or read book Encyclopedia of Organizational Knowledge, Administration, and Technology written by Khosrow-Pour D.B.A., Mehdi and published by IGI Global. This book was released on 2020-09-29 with total page 2734 pages. Available in PDF, EPUB and Kindle. Book excerpt: For any organization to be successful, it must operate in such a manner that knowledge and information, human resources, and technology are continually taken into consideration and managed effectively. Business concepts are always present regardless of the field or industry – in education, government, healthcare, not-for-profit, engineering, hospitality/tourism, among others. Maintaining organizational awareness and a strategic frame of mind is critical to meeting goals, gaining competitive advantage, and ultimately ensuring sustainability. The Encyclopedia of Organizational Knowledge, Administration, and Technology is an inaugural five-volume publication that offers 193 completely new and previously unpublished articles authored by leading experts on the latest concepts, issues, challenges, innovations, and opportunities covering all aspects of modern organizations. Moreover, it is comprised of content that highlights major breakthroughs, discoveries, and authoritative research results as they pertain to all aspects of organizational growth and development including methodologies that can help companies thrive and analytical tools that assess an organization’s internal health and performance. Insights are offered in key topics such as organizational structure, strategic leadership, information technology management, and business analytics, among others. The knowledge compiled in this publication is designed for entrepreneurs, managers, executives, investors, economic analysts, computer engineers, software programmers, human resource departments, and other industry professionals seeking to understand the latest tools to emerge from this field and who are looking to incorporate them in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to business, management science, organizational development, entrepreneurship, sociology, corporate psychology, computer science, and information technology will benefit from the research compiled within this publication.
Book Synopsis Data mining techniques in financial fraud detection by : Rohan Ahmed
Download or read book Data mining techniques in financial fraud detection written by Rohan Ahmed and published by GRIN Verlag. This book was released on 2018-05-24 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seminar paper from the year 2016 in the subject Computer Science - General, grade: 1.7, Heilbronn University, language: English, abstract: In this seminar thesis you will get a view about the Data Mining techniques in financial fraud detection. Financial Fraud is taking a big issue in economical problem, which is still growing. So there is a big interest to detect fraud, but by large amounts of data, this is difficult. Therefore, many data mining techniques are repeatedly used to detect frauds in fraudulent activities. Majority of fraud area are Insurance, Banking, Health and Financial Statement Fraud. The most widely used data mining techniques are Support Vector Machines (SVM), Decision Trees (DT), Logistic Regression (LR), Naives Bayes, Bayesian Belief Network, Classification and Regression Tree (CART) etc. These techniques existed for many years and are used repeatedly to develop a fraud detection system or for analyze frauds.
Book Synopsis Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques by : Bart Baesens
Download or read book Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques written by Bart Baesens and published by John Wiley & Sons. This book was released on 2015-07-27 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementation. Coverage includes data gathering, preprocessing, model building, and post-implementation, with comprehensive guidance on various learning techniques and the data types utilized by each. These techniques are effective for fraud detection across industry boundaries, including applications in insurance fraud, credit card fraud, anti-money laundering, healthcare fraud, telecommunications fraud, click fraud, tax evasion, and more, giving you a highly practical framework for fraud prevention. It is estimated that a typical organization loses about 5% of its revenue to fraud every year. More effective fraud detection is possible, and this book describes the various analytical techniques your organization must implement to put a stop to the revenue leak. Examine fraud patterns in historical data Utilize labeled, unlabeled, and networked data Detect fraud before the damage cascades Reduce losses, increase recovery, and tighten security The longer fraud is allowed to go on, the more harm it causes. It expands exponentially, sending ripples of damage throughout the organization, and becomes more and more complex to track, stop, and reverse. Fraud prevention relies on early and effective fraud detection, enabled by the techniques discussed here. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques helps you stop fraud in its tracks, and eliminate the opportunities for future occurrence.
Book Synopsis Handbook of Massive Data Sets by : James Abello
Download or read book Handbook of Massive Data Sets written by James Abello and published by Springer. This book was released on 2013-12-21 with total page 1209 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proliferation of massive data sets brings with it a series of special computational challenges. This "data avalanche" arises in a wide range of scientific and commercial applications. With advances in computer and information technologies, many of these challenges are beginning to be addressed by diverse inter-disciplinary groups, that indude computer scientists, mathematicians, statisticians and engineers, working in dose cooperation with application domain experts. High profile applications indude astrophysics, bio-technology, demographics, finance, geographi cal information systems, government, medicine, telecommunications, the environment and the internet. John R. Tucker of the Board on Mathe matical Seiences has stated: "My interest in this problern (Massive Data Sets) isthat I see it as the rnost irnportant cross-cutting problern for the rnathernatical sciences in practical problern solving for the next decade, because it is so pervasive. " The Handbook of Massive Data Sets is comprised of articles writ ten by experts on selected topics that deal with some major aspect of massive data sets. It contains chapters on information retrieval both in the internet and in the traditional sense, web crawlers, massive graphs, string processing, data compression, dustering methods, wavelets, op timization, external memory algorithms and data structures, the US national duster project, high performance computing, data warehouses, data cubes, semi-structured data, data squashing, data quality, billing in the large, fraud detection, and data processing in astrophysics, air pollution, biomolecular data, earth observation and the environment.
Book Synopsis Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection by : Koyuncugil, Ali Serhan
Download or read book Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection written by Koyuncugil, Ali Serhan and published by IGI Global. This book was released on 2010-09-30 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection has never been more important, as the research this book presents an alternative to conventional surveillance and risk assessment. This book is a multidisciplinary excursion comprised of data mining, early warning systems, information technologies and risk management and explores the intersection of these components in problematic domains. It offers the ability to apply the most modern techniques to age old problems allowing for increased effectiveness in the response to future, eminent, and present risk.
Book Synopsis Data Mining for Intelligence, Fraud & Criminal Detection by : Christopher Westphal
Download or read book Data Mining for Intelligence, Fraud & Criminal Detection written by Christopher Westphal and published by CRC Press. This book was released on 2008-12-22 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 2004, the Government Accountability Office provided a report detailing approximately 200 government-based data-mining projects. While there is comfort in knowing that there are many effective systems, that comfort isn‘t worth much unless we can determine that these systems are being effectively and responsibly employed.Written by one of the most
Book Synopsis Fraud Detection in White-Collar Crime by : Rohan Ahmed
Download or read book Fraud Detection in White-Collar Crime written by Rohan Ahmed and published by GRIN Verlag. This book was released on 2018-06-28 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bachelor Thesis from the year 2017 in the subject Computer Science - Commercial Information Technology, grade: 1.3, Heilbronn University, language: English, abstract: White-collar crime is and has always been an urgent issue for the society. In recent years, white-collar crime has increased dramatically by technological advances. The studies show that companies are affected annually by corruption, balance-sheet manipulation, embezzlement, criminal insolvency and other economic crimes. The companies are usually unable to identify the damage caused by fraudulent activities. To prevent fraud, companies have the opportunity to use intelligent IT approaches. The data analyst or the investigator can use the data which is stored digitally in today’s world to detect fraud. In the age of Big Data, digital information is increasing enormously. Storage is cheap today and no longer a limited medium. The estimates assume that today up to 80 percent of all operational information is stored in the form of unstructured text documents. This bachelor thesis examines Data Mining and Text Mining as intelligent IT approaches for fraud detection in white-collar crime. Text Mining is related to Data Mining. For a differentiation, the source of the information and the structure is important. Text Mining is mainly concerned with weak- or unstructured data, while Data Mining often relies on structured sources. At the beginning of this bachelor thesis, an insight is first given on white-collar crime. For this purpose, the three essential tasks of a fraud management are discussed. Based on the fraud triangle of Cressey it is showed which conditions need to come together so that an offender commits a fraudulent act. Following, some well-known types of white-collar crime are considered in more detail. Text Mining approach was used to demonstrate how to extract potentially useful knowledge from unstructured text. For this purpose, two self-generated e-mails were converted into struc-tured format. Moreover, a case study will be conducted on fraud detection in credit card da-taset. The dataset contains legitimate and fraudulent transactions. Based on a literature research, Data Mining techniques are selected and then applied on the dataset by using various sampling techniques and hyperparameter optimization with the goal to identify correctly pre-dicted fraudulent transactions. The CRISP-DM reference model was used as a methodical procedure.
Author :Society for Industrial and Applied Mathematics Publisher :Society for Industrial and Applied Mathematics (SIAM) ISBN 13 :9780898714340 Total Pages :1024 pages Book Rating :4.7/5 (143 download)
Book Synopsis Proceedings of the Tenth Annual ACM-SIAM Symposium on Discrete Algorithms by : Society for Industrial and Applied Mathematics
Download or read book Proceedings of the Tenth Annual ACM-SIAM Symposium on Discrete Algorithms written by Society for Industrial and Applied Mathematics and published by Society for Industrial and Applied Mathematics (SIAM). This book was released on 1999 with total page 1024 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation This volume contains 93 traditional papers and 74 short form abstracts presented at the January 1999 symposium, which encouraged increased participation from the discrete mathematics community this year. Topics of the longer papers include page replacement for general caching problems, queries with segments in Voronoi diagrams, clustering in large graphs and matrices, the complexity of gene placement, and indexing schemes for random points. Some of the short paper topics are locked and unlocked polygonal chains in 3D, compact roundtrip routing for digraphs, and sampling spin configurations on an Ising system. No subject index. Annotation copyrighted by Book News, Inc., Portland, OR.
Author :Management Association, Information Resources Publisher :IGI Global ISBN 13 :1466624566 Total Pages :2335 pages Book Rating :4.4/5 (666 download)
Book Synopsis Data Mining: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources
Download or read book Data Mining: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2012-11-30 with total page 2335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining continues to be an emerging interdisciplinary field that offers the ability to extract information from an existing data set and translate that knowledge for end-users into an understandable way. Data Mining: Concepts, Methodologies, Tools, and Applications is a comprehensive collection of research on the latest advancements and developments of data mining and how it fits into the current technological world.
Book Synopsis Introduction to Data Mining and Its Applications by : S. Sumathi
Download or read book Introduction to Data Mining and Its Applications written by S. Sumathi and published by Springer Science & Business Media. This book was released on 2006-09-26 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, AI, machine learning, NN, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization. This book is intended for a wide audience of readers who are not necessarily experts in data warehousing and data mining, but are interested in receiving a general introduction to these areas and their many practical applications. Since data mining technology has become a hot topic not only among academic students but also for decision makers, it provides valuable hidden business and scientific intelligence from a large amount of historical data. It is also written for technical managers and executives as well as for technologists interested in learning about data mining.
Book Synopsis Advances on Data Mining: Applications and Theoretical Aspects by : Petra Perner
Download or read book Advances on Data Mining: Applications and Theoretical Aspects written by Petra Perner and published by Springer Science & Business Media. This book was released on 2011-08-09 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th Industrial Conference on Data Mining, ICDM 2011, held in New York, USA in September 2011. The 22 revised full papers presented were carefully reviewed and selected from 100 submissions. The papers are organized in topical sections on data mining in medicine and agriculture, data mining in marketing, data mining for Industrial processes and in telecommunication, Multimedia Data Mining, theoretical aspects of data mining, Data Warehousing, WebMining and Information Mining.
Book Synopsis Advances in Data Mining by : Petra Perner
Download or read book Advances in Data Mining written by Petra Perner and published by Springer Science & Business Media. This book was released on 2006-06-30 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th Industrial Conference on Data Mining, ICDM 2006, held in Leipzig, Germany in July 2006. Presents 45 carefully reviewed and revised full papers organized in topical sections on data mining in medicine, Web mining and logfile analysis, theoretical aspects of data mining, data mining in marketing, mining signals and images, and aspects of data mining, and applications such as intrusion detection, and more.
Book Synopsis Investigative Data Mining for Security and Criminal Detection by : Jesus Mena
Download or read book Investigative Data Mining for Security and Criminal Detection written by Jesus Mena and published by Butterworth-Heinemann. This book was released on 2003 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher Description
Book Synopsis Computational Intelligence in Data Mining by : Himansu Sekhar Behera
Download or read book Computational Intelligence in Data Mining written by Himansu Sekhar Behera and published by Springer. This book was released on 2017-05-19 with total page 825 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents high quality papers presented at the International Conference on Computational Intelligence in Data Mining (ICCIDM 2016) organized by School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India during December 10 – 11, 2016. The book disseminates the knowledge about innovative, active research directions in the field of data mining, machine and computational intelligence, along with current issues and applications of related topics. The volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science.
Book Synopsis Real-time Fraud Detection Analytics on IBM System z by : Mike Ebbers
Download or read book Real-time Fraud Detection Analytics on IBM System z written by Mike Ebbers and published by IBM Redbooks. This book was released on 2013-04-11 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt: Payment fraud can be defined as an intentional deception or misrepresentation that is designed to result in an unauthorized benefit. Fraud schemes are becoming more complex and difficult to identify. It is estimated that industries lose nearly $1 trillion USD annually because of fraud. The ideal solution is where you avoid making fraudulent payments without slowing down legitimate payments. This solution requires that you adopt a comprehensive fraud business architecture that applies predictive analytics. This IBM® Redbooks® publication begins with the business process flows of several industries, such as banking, property/casualty insurance, and tax revenue, where payment fraud is a significant problem. This book then shows how to incorporate technological advancements that help you move from a post-payment to pre-payment fraud detection architecture. Subsequent chapters describe a solution that is specific to the banking industry that can be easily extrapolated to other industries. This book describes the benefits of doing fraud detection on IBM System z®. This book is intended for financial decisionmakers, consultants, and architects, in addition to IT administrators.
Book Synopsis Multiple Additive Regression Trees a Methodology for Predictive Data Mining for Fraud Detection by : Antonio J. F. DA Silva Monteiro
Download or read book Multiple Additive Regression Trees a Methodology for Predictive Data Mining for Fraud Detection written by Antonio J. F. DA Silva Monteiro and published by . This book was released on 2002-09 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Defense Finance Accounting Service DFAS-Operation Mongoose (Internal Review - Seaside) is using new and innovative techniques for fraud detection. Their primary techniques for fraud detection are the data mining tools of classification trees and neural networks as well as methods for pooling the results of multiple model fits. In this thesis a new data mining methodology, Multiple Additive Regression Trees (MART) is applied to the problem of detecting potential fraudulent and suspect transactions (those with conditions needing improvement - CNI's). The new MART methodology is an automated method for pooling a "forest" of hundreds of classification trees. This study shows how MART can be applied to fraud data. In particular it shows how MART identified classes of important variables and that MART is as effective with iaw input variables as it is with the categorical variables currently constructed individually by DFAS. MART is also used to explore the effects of the substantial amount of missing data in the historical fraud database. In general MART is as accurate as existing methods, requires much less effort to implement saving many man days, handles missing values in a sensible and transparent way, and provides features such as identifying more important variables.
