Data Mining for Intelligence, Fraud & Criminal Detection: Advanced Analytics & Information Sharing Technologies Review

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Data Mining for Intelligence, Fraud & Criminal Detection: Advanced Analytics & Information Sharing Technologies ReviewEver encounter a concept so revolutionary that you wonder why everyone isn't talking about it? Data Mining for Intelligence, Fraud, & Criminal Detection (CRC Press 2009), by Christopher Westphal, is like that.
Admittedly, only the few, the proud, and the discerning might dare to look beyond a title and trappings ostensibly geared for hardcore law-enforcement types and techies who live and die by visual analytics and pattern recognition for crime detection and fraud prevention. Yet "Data Mining" is not only eminently readable, it contains a game-changing message practically akin to the Rosetta Stone, on how to extract sense and sensibility from all the petabytes of information and data piling up in "cylinders of excellence" (one insider's waggish term for stovepiped data) around us.
Seriously, if the content in Data Mining's pages (think of it as a 2-1/2 pound stimulus package) could be funneled to, say, Obama, Oprah, and a certain researcher at the Library of Congress, we could look forward to pole-vaulting our way through progress to peaceful prosperity - raising our quality of life while saving (as opposed to spending) billions in the process. Let's put it this way: if you like anything at all about Numb3rs, or even NCIS (the most-viewed series in America - hey, at least we've made a few steps up from Baywatch), CSI, or shows of that ilk - you owe yourself a crack at Westphal's Data Mining book. Plus, it'll give your biceps a workout, and impress the heck out of onlookers. Not to mention which, all proceeds go to the National Law Enforcement Officers Memorial Fund, which speaks well for the author's motives on more than one front, not to mention his credibility.Data Mining for Intelligence, Fraud & Criminal Detection: Advanced Analytics & Information Sharing Technologies Overview

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Internet Searches for Vetting, Investigations, and Open-Source Intelligence Review

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Internet Searches for Vetting, Investigations, and Open-Source Intelligence ReviewI have been a private investigator for more than 25 years. When I started in this business computers were scarce and the Internet had not yet been commercialized. Everything was done with a pencil and telephone. I have a lot of experience so it is hard for me to find books that are useful. I buy books hoping to learn one or two new things. Edward J. Appel, a retired FBI agent is the author. His company has done work for me so I knew the quality of his work and assumed his book would be at the same level as his investigative efforts. I wasn't disappointed.
The book is 320 pages and broken into 4 sections. Appel begins with a chapter about behavior and technology which orients the investigator/analyst on the growth and use of the Internet. He discusses the usefulness of the Internet as an investigative tool and the transformations the Internet is making through social and technological advances. Along with the benefits for investigators comes the darker side of the web, and Appel examines its criminal exploitation.
The first section provides a great introduction and is geared toward corporate investigators and security personnel tasked with monitoring IT systems, vetting employees and guarding company intellectual property. In Section 2 Appel outlines legal and policy issues related to using information from the Internet in investigations. He identifies liability and privacy issues and laws addressing these concerns such as the Fair Credit Reporting Act. He also dedicates a chapter to litigation, defamation, and invasion of privacy torts.
Appel develops a framework for preparation and planning of successful Internet research. He covers basic information about search engines, metasearch engines, social networking sites and search terms.
I found the chapters Automation of Searching and Internet Intelligence Reporting to be the most enlightening. Reducing time spent searching and analyzing information, seems like a no-brainer. But I would bet the number of investigators who have looked for automated solutions to their collection efforts is small. The Internet Intelligence Reporting section recommends the format and organization of a report as well as what to include and how to cite sources.
Internet Searches for Vetting, Investigations, and Open-Source Intelligence, like many trade publications, is on the pricey side. However it delivers with content and is an easy read. It met my criteria for a successful investigations book because I learned much more than two new things.
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Mining the Web: Discovering Knowledge from Hypertext Data Review

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Mining the Web: Discovering Knowledge from Hypertext Data ReviewExecutive summary: This is a fabulous book, written with care and
precision, easy to read yet covering in detail a wide variety of
the most beautiful and promising developments in data mining and
machine learning as it relates to the World Wide Web, including a
prescient vision of where the field is headed in the future.
More detail: There are science authors who are clear experts in
their field, yet have trouble communicating their knowledge. Then
there are science authors who write with clarity, but achieve it
by dumbing down technical details to cater to a broad readership.
Finally, there are authors who are experts and leaders in their
field, who are actively contributing to the forefront of research,
who are excellent writers, and who can communicate complex
concepts to a diverse audience with acumen, without glossing over
important details. Soumen Chakrabarti is one such author. "Mining
the Web" is a stunning achievement. It is an excellent summary of
the past decade or so of research in the area, covering nearly all
of the important bases, including the machinery of Web crawling,
Web information retrieval (i.e., search engines), clustering,
automated classification, semi-supervised approaches, social
network analysis, and focused crawling. Though Chakrabarti himself
has contributed prominently to the field, this book is not at all
the vehicle for self-promotion that other specialist texts
sometimes feel like. The book should be valuable to newcomers,
students, and experts alike, and could certainly serve as an
excellent course textbook. High-level concepts can be grasped with
little mathematical background, yet more technically sophisticated
readers will not be disappointed: most topics do include rigorous
coverage. The text is well organized, well written, and well
conceived. It's design, including generous and illuminating
figures and illustrations, possesses an artist's touch, perhaps
not surprising given that Chakrabarti designs his own font
libraries in his (apparently scant) spare time. It's hard to
imagine where Chakrabarti found the time to write such a
comprehensive and thoughtful book, but I'm not asking any
questions: I'm thrilled with the outcome. The book is a must-have
reference for anyone working in -- or aspiring to work in -- the
crossroads of Web algorithmics, data mining, and machine learning.
David M. Pennock
Senior Research Scientist, Overture Services, Inc.
[website]Mining the Web: Discovering Knowledge from Hypertext Data Overview

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Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications) Review

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Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications) ReviewSo what does the author, Bing Liu know about Web data mining to write the book "Web Data Mining - Exploring Hyperlinks, Contents, and Usage Data"[1] ? Fortunately the answer is "a lot!" This fact along with the title which had some cosine similarity with the names of my research lab and a graduate course that I have been teaching at the University of Louisville since 2004, and prior to that at the University of Memphis since 2000, are the reasons why I ordered a copy of this book. Bing Liu is a well seasoned researcher who has made significant contributions to association rule mining, in particular classification using association rule mining and association rule mining with multiple supports. He has also worked on Web data extraction, and more recently on opinion mining. In addition to the expertise of the author, two of the chapters, Chapter 8, Web Crawling, and Chapter 12, Web Usage Mining, were contributed by two leading experts in these respective areas, Filippo Menczer for the former and Bamshad Mobasher for the latter.
This book is appropriate for students at the graduate or senior undergraduate level, for practitioners in industry, and even as a good comprehensive reference for researchers in academia.
The Table of Contents held a surprise for someone who had always found it hard to limit the number of textbooks to one book in a web mining course that does not have data mining as prerequisite, and thus typically prescribes a good data mining book to introduce data mining techniques, in addition to a second book related to web mining. This book, on the other hand, has two parts, one devoted to data mining, and the other devoted to Web mining. While it was not a problem to find a very good data mining book (I have a few of them on my bookshelf), it was harder to find a book that addressed data mining and Web mining. It was also hard to find a good and comprehensive Web mining book, since most of them tend to focus on one or only two of the three main Web mining areas of Web structure, content, and usage mining (typically leaving Web usage mining in the dark, with just a small section, citing that it is an emerging area). This book, on the other hand, is a serious book on Web mining that also devotes a decent portion to data mining. I would describe the way the topics are presented as deep and rigorous enough in most chapters, which is in contrast to a large number of books on data mining and web mining. That said, because the book is full of simple examples that illustrate the methods being discussed, it is useful even for beginners, making it also appropriate for an introductory level course.
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Counterterrorism and Open Source Intelligence (Lecture Notes in Social Networks) Review

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Counterterrorism and Open Source Intelligence (Lecture Notes in Social Networks) ReviewI anticipate that a paperback version will be offered at a more affordable price for individuals--this is the library or institutional "trade" price.
I am very glad to see the publisher make use of Look Inside the Book, and encourage all interested parties to use that feature and study the table of contents. I have to articulate my profound respect for the conference organizer and senior book editor and for those contributing to this book, all of whom I met at the conference for which this content was created.
I have never seen a better collection of scientific and mathematical approaches to leveraging open sources of information to identify precursors and patterns of terrorism. This is an original book, and the first major effort of the new counterterrorism center at the University of Southern Denmark.
Including my alternative perspective, as one other senior participant put it, "makes our job harder." One reason I particularly like Nordic professionals is because of their integrity. There is a great deal of intelligence and total integrity in this book; it is an honor for me to have been included. I am not competent in the way the other authors are, and my regard for their pioneering is unlimited.
Also just published, very US centric but a really original study, is No More Secrets: Open Source Information and the Reshaping of U.S. Intelligence (Praeger Security International). I have provided a lengthy review at the Amazon page for that book.
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Social Network Data Analytics Review

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Social Network Data Analytics ReviewThis is a very interesting book for both researchers and practitioners in computer science who work in the area of data mining and want to learn the state-of-the-art in social network data analytics. The book provides good coverage of the subject area by focusing on popular research topics, such as the study of the statistical properties that are apparent in "typical" social networks, the problems of community detection and social influence analysis, the expert-location discovery problem, the privacy issues that arise in the context of social networks, as well as visualization techniques, text mining techniques and social tagging. The emerging area of integrating sensors and social networks is also examined. Each chapter of the book contains numerous bibliographic references that will guide readers who are interested in particular topics to explore these topics in more depth. Overall, I highly recommend this book!Social Network Data Analytics Overview

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Social Network Analysis: A Handbook Review

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Social Network Analysis: A Handbook ReviewAs a biostatistician interested in learning some social network analysis, I was immediately attracted to this book. It is short and non-technical and seemed to provide an overview of the key issues in this research area. Once I began to read it, I quickly saw that Scott has a gift for presenting complex idea in clear prose. (I don't know quite why it is, but British academics are typically very good at expository prose.) In any case, Social Network Analysis provided just what I wanted -- a quick (180 page) overview that will help me move on to other, more technical works in this area.
Bravo!Social Network Analysis: A Handbook Overview

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