Customer Reviews (1)

ALMOST EVERYTHING A PROSPECTOR IN WASHINGTON NEEDS TO KNOW.
LOTS OF HISTORICAL INFORMATION AND STORIES FROM THE "OLD TIMERS" . THE BOOK IS VERY WELL THOUGHT OUT AND PUT TOGETHER. THE INFORMATION IN THIS BOOK PROVIDES MODERN RECREATIONAL PROSPECTORS WITH INFORMATION ONWHERE TO GO BY LETTING YOU KNOW WHERE GOLD WAS FOUND IN THE PAST. ... Read more

Product Description
Examines environmental conflicts between mining companies and indigenous communities and offers a comparative study of the factors leading to those conflicts. Ali presents four cases from the United States and Canada that exemplify different historical relationships with government and industry and provide an instance of high and low levels of Native resistance in each country. Through these cases, Ali analyzes why and under what circumstances tribes agree to negotiated mining agreements on their lands, and why some negotiations are successful and others not.

“It is refreshing to find a strong work grounded in social science theory that is also engaging for casual readers.” —Montana, the Magazine of Western History

“An important contribution to our understanding of the factors influencing decision making among these groups in both nations.” —Ken Pepion, Harvard University Native American Studies Program ... Read more

Product Description
An Introduction to Mining Seismology describes comprehensively the modern methods and techniques used to monitor and study seismicity and rockbursts in mines. Key case histories from various worldwide mining districts clearly illustrate and skillfully emphasize the practical aspects of mining seismology. This text is intended as a handbook for geophysicists and mining and rock mechanics engineers working at mines. It will alsoserve as an essential reference tool for seismologists working at research institutions on local seismicity not necessarily induced by mining.

Key Features
* Presents a comprehensive description of seismicity induced by mining worldwide
* Provides information on optimum network planning and seismic event location procedures in deep mines
* Covers a broad array of topics including focal mechanism, moment tensor, and double-couple versus non-double-couple seismic events in mines
* Includes data on source parameters and scaling relations for seismic events in mines ... Read more

Product Description

Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas.

This book explains and explores the principal techniques of Data Mining: for classification, generation of association rules and clustering. It is written for readers without a strong background in mathematics or statistics and focuses on detailed examples and explanations of the algorithms given. This should prove of value to readers of all kinds, from those whose only use of data mining techniques will be via commercial packages right through to academic researchers.

This book aims to help the general reader develop the necessary understanding to use commercial data mining packages discriminatingly, as well as enabling the advanced reader to understand or contribute to future technical advances in the field. Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included.

Customer Reviews (2)

Introduction
This is an undergraduate introduction to data mining. The book doesn't go into details. It may be suitable for people who want to get a quick feel of the data mining field. People who need more details shall read more serious and comprehensive introductions. Overall I am giving 4 stars, because I liked it.

excellent introduction
This book is an excellent introduction to data mining, concentrating primarily on decision tree induction. The material provided is presented clearly with no assumption of prior knowledge on the part of the reader. A weakness of the book is that it doesn't place the material provided within the larger context of machine learning, both in terms of breadth or depth. However, when used as a textbook the instructor could easily address this problem. ... Read more

Product Description
Placer mining companies revolutionized the mining industry during the late nineteenth century when they first put dredges to work on previously unprofitable ground.Dredges would so effectively mine gold-bearing grounds, one forecaster predicted in 1903, that the world would "not only be saturated with gold, it would be nauseated with it."In The Conrey Placer Mining Company, historian Clark C. Spence describes the optimistic hopes of the dredge miners in Virginia City, Montana, and the hard realities of this new industrial placer mining technology. Since 1863, miners had pulled millions of dollars in gold out of Montana's Alder Gulch using pans and Long Toms and later tunnels and ground sluices.But dredging was a dramatically different process.The most costly of all placer mining techniques, dredging was a highly industrial and technological enterprise.Spence describes how the dredges, as large as ocean freighters and costing hundreds of thousands of dollars each, dug their own ponds as they moved ponderously down the gulch, ripping up paydirt from bedrock as deep as a hundred feet below the surface.He shows how the efficiency and power of this revolutionary, "mass production" technology changed the mining industry and how it irrevocably altered the western landscape. Using corporate papers held by Harvard University's Baker Library, Spence recounts the story of the Conrey Placer Mining Company.In many ways, it is the story of the early years of the American gold-dredging industry.As the pre-eminent Montana placer firm of the early twentieth century, Conrey's operations showed a continuity common to only a handful of multiple-dredge concerns.The company tested different types of dredged, innovatively adapted them to the special conditions of Montana's climate and terrain, and later adopted state-of-the-art California-type dredges.Spence takes a penetrating look at this unique company, which operated so successfully in the isolation of Montana's southwestern mountains.This volume is at once a corporate history, a technological history, and a local history that takes readers through the intricate workings of an innovative mining company and examines the lives of the executives, the engineers, and the workers who made it possible. ... Read more

Product Description

Managing and Mining Graph Data is a comprehensive survey book in graph data analytics. It contains extensive surveys on important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy. It also studies a number of domain-specific scenarios such as stream mining, web graphs, social networks, chemical and biological data. The chapters are written by leading researchers, and provide a broad perspective of the area. This is the first comprehensive survey book in the emerging topic of graph data processing.

Managing and Mining Graph Data is designed for a varied audience composed of professors, researchers and practitioners in industry. This volume is also suitable as a reference book for advanced-level database students in computer science.

About the Editors:

Charu C. Aggarwal obtained his B.Tech in Computer Science from IIT Kanpur in 1993 and Ph.D. from MIT in 1996. He has worked as a researcher at IBM since then, and has published over 130 papers in major data mining conferences and journals. He has applied for or been granted over 70 US and International patents, and has thrice been designated a Master Inventor at IBM. He has received an IBM Corporate award for his work on data stream analytics, and an IBM Outstanding Innovation Award for his work on privacy technology. He has served on the executive committees of most major data mining conferences. He has served as an associate editor of the IEEE TKDE, as an associate editor of the ACM SIGKDD Explorations, and as an action editor of the DMKD Journal. He is a fellow of the IEEE, and a life-member of the ACM.

Haixun Wang is currently a researcher at Microsoft Research Asia. He received the B.S. and the M.S. degree, both in computer science, from Shanghai Jiao Tong University in 1994 and 1996. He received the Ph.D. degree in computer science from the University of California, Los Angeles in 2000. He subsequently worked as a researcher at IBM until 2009. His main research interest is database language and systems, data mining, and information retrieval. He has published more than 100 research papers in referred international journals and conference proceedings. He serves as an associate editor of the IEEE TKDE, and has served as a reviewer and program committee member of leading database conferences and journals.

Customer Reviews (1)

Worth every penny.
Written by leading researchers, Managing and Mining Graph Data is a well-structured, comprehensive guide to graph data. Highly recommended! ... Read more

Product Description
(Pearson Education) Provides an understanding of what shared service is. Outlines how to assess its viability for an organization and how to proceed with planning and implementing it. ... Read more

Customer Reviews (1)

Moving Internal Services to a Market Economy
Moving Internal Services from Soviet-Style Monopoly to a Market System

This book is an excellent introduction to the implementation of shared services by people with lots of pragmatic experience. It's required reading at my company.

If you are just starting out, it provides a good map of what shared services are and how to go about implementing. If you have done it, it might remind you of the original vision.

Also, the book is well written, making it easy and enjoyable to read--which means that I actually read it instead of leaving it on the table hoping for osmosis to kick in.

As someone involved the creation of software to automate and support shared services at Newscale, I found the focus on "running Shared Services as business" (and all that implies) the clearest difference between the new way and the old way.

This means, frankly, that while cutting costs is the primary driver for shared services, the path has to take account fiveelements that are non-obvious today: 1) how do I plan and execute my service workflows, 2) how do I enable my internal customers to procure my offers and those of outsourcers? 3) how do I manage the business relationship with the business units, 4)how do I charge for services and manage the Shared Services business unit), 5) how do I design and create my service "products"?

In other words, run a business that produces value for customers at a profit -- just like a market economy. Which sounds obvious and simple, but it's not. Just ask the Russians...or the dotcoms. ... Read more

Product Description

The second edition, containing 28,500 terms, incorporates the technological developments and environmental regulations that have changed the minerals industry so dramatically. It is the culmination of a 5-year effort incorporating not only standard mining-related terms but also terms in peripheral areas, such as the environment, marine mining, leaching, pollution, automation, health and safety. Many of these terms now have a legal definition based on law or regulation.

Customer Reviews (1)

Permanently open on my desk!
This is an essential reference for any budding mining engineer or geologist and even for experienced professionals.

There is no better reference available that I am aware of.

The only minor criticism that I have is that it is biassed towards USA terminology rather than adopting global terminology, but that is quite understandable. ... Read more

Product Description
Data mining enables you to discover valuable hidden information in your data and use it to solve your business problems. This introductory guide to data mining uses a case study approach that takes you through the SAS Enterprise Miner interface from initial data access to several completed analyses, such as predictive modeling, clustering analysis, association analysis, and link analysis. If you are a new SAS Enterprise Miner user, you will find this friendly guide to be an invaluable resource as you navigate the interface. After completing the case studies in this guide, you will be prepared to tackle the more complicated statistical analyses that are covered in the SAS Enterprise Miner online reference documentation. ... Read more

Customer Reviews (2)

Sas Mining
Another must by for any level Sas user!Real world examples are the best way to learn.Another great buy!

Fast learning.
If you want or need to quick learn SAS Enterprise miner, this is very good opportunity to do that. At first, you get basic info about included functions and after that you go through good described case studies. ... Read more

Product Description
The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications.

• Introduces data mining methods and applications.
• Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods.
• Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining.
• Features detailed case studies based on applied projects within industry.
• Incorporates discussion of data mining software, with case studies analysed using R.
• Is accessible to anyone with a basic knowledge of statistics or data analysis.
• Includes an extensive bibliography and pointers to further reading within the text.

Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance. ... Read more

Product Description
California’s official Gold Rush ghost town lives again in this vivid account.

The Bodie Mining District was established in 1860 after the discovery of gold deposits in the area. The boom ended just twenty years later, and the town began its long, slow decline, surviving into the twentieth century as a small town supported by a few small but steady mines. Mining ended with World War II. What remained of the town became a state park in 1964.

In Bodie’s Gold, author Marguerite Sprague uncovers the original sources for information whenever possible, from the first mining claims to interviews with Bodieites alive today. Sprague has traced several popular Bodie legends back to their original sources, leading to revisions of beloved myths, more details about some others and a few interesting new stories. Enhanced with numerous historic photographs and quotations from newspapers of that period, as well as by the reminiscences of former residents, Bodie’s Gold offers a fascinating account of life in a Gold Rush boomtown. ... Read more

Customer Reviews (3)

A well-written, well-researched, scholarly work that also recognizes the native Paiute.
I found this to be a very informative book.Sprague's book includes 10 pages of references, footnotes, wonderful appendices, and an excellent index--not to mention several photos.Sprague was incredibly thorough in her research, and she spent more time discussing the Kutzadika Paiute and their lives than any other publication about Bodie than I've read to date.This book is a must read for anyone interested in the history of Bodie.

Simply a brillant book written on the Bodie mines
Mr Piatt spent a lot of time researching for this book and it definately shows and is very informative of the history of mining in Bodie with great photos. A must have definately.

Compelling California history, with heart!
This is an excellent book, obviously a work of intense research and profound appreciation for the town and people of Bodie, California.The author touches upon myriad aspects of the town's development and decline, including anthropology, technology, and geology.The book also deals with the human side of this hard-scrabble community, and includes many personal reflections of actual Bodieites.The author also infuses the book with a unique sense of humor, which perfectly suits the subject matter.Highly recommended! ... Read more

Product Description
Data Mining for Genomics and Proteomics uses pragmatic examples and a complete case study to demonstrate step-by-step how biomedical studies can be used to maximize the chance of extracting new and useful biomedical knowledge from data. It is an excellent resource for students and professionals involved with gene or protein expression data in a variety of settings. ... Read more

Customer Reviews (1)

Excellent Introduction - Packed with Information
Excellent book on data mining genomic and proteomics! Very practical with clear direction on how to analyze this type of data, from the basic terminology of the field to more advanced methods. Impressed with the amount of information packed into the pages and how clearly complicated topics (general data mining as well as biological) are presented. Highly recommended! ... Read more

Product Description
Ensemble methods have been called the most influential development in Data Mining and Machine Learning in the past decade. They combine multiple models into one usually more accurate than the best of its components. Ensembles can provide a critical boost to industrial challenges -- from investment timing to drug discovery, and fraud detection to recommendation systems -- where predictive accuracy is more vital than model interpretability.

Ensembles are useful with all modeling algorithms, but this book focuses on decision trees to explain them most clearly. After describing trees and their strengths and weaknesses, the authors provide an overview of regularization -- today understood to be a key reason for the superior performance of modern ensembling algorithms. The book continues with a clear description of two recent developments: Importance Sampling (IS) and Rule Ensembles (RE). IS reveals classic ensemble methods -- bagging, random forests, and boosting -- to be special cases of a single algorithm, thereby showing how to improve their accuracy and speed. REs are linear rule models derived from decision tree ensembles. They are the most interpretable version of ensembles, which is essential to applications such as credit scoring and fault diagnosis. Lastly, the authors explain the paradox of how ensembles achieve greater accuracy on new data despite their (apparently much greater) complexity.

This book is aimed at novice and advanced analytic researchers and practitioners -- especially in Engineering, Statistics, and Computer Science. Those with little exposure to ensembles will learn why and how to employ this breakthrough method, and advanced practitioners will gain insight into building even more powerful models. Throughout, snippets of code in R are provided to illustrate the algorithms described and to encourage the reader to try the techniques. ... Read more

Customer Reviews (3)

really helpful in learning the method
During my 10 plus years of modeling experience, I have always paid most of my attention on variable selection, predictive power, effectiveness and efficiency of a single model form such as logistic model, ordinary regression, tree, etc. From time to time, I also segment my sample space into pieces and then apply different modeling techniques. Never really aware of the concept of 'model selection' or 'model combination'. That classical approach has served me well. But I always suspected that there was a better approach to combine different methods to get better predictions.
Ensemble methods detailed in this books gave me the 'ah ha'. It gave a nicely balanced flavor of easy implementation and difficult concepts. I really enjoyed the book. I was able to finish the book quick and would save it for reference.
If there is anything that I would want to see in more detail, it is the treatment of evaluation of model prediction. It is a bit light on how to tell if the final product is really working. Given that the book is an intro, then it is not really a mis-treatment.
overall, awesome small book.

The definitive reference on ever-important ensemble models
The definitive reference on ensembles, which are a central, profound aspect of predictive modeling best practices. A solid, core, important reference with great coverage and tutorial value.

A much needed guide to ensemble methods
"Ensemble Methods in Data Mining" (EMIDM) is an excellent introduction and reference to ensemble methods, from several perspectives:

- good mathematical descriptions of the algorithms;
- intuitive explanations of the concepts involved;
- several illustrative examples (including R code); and
- a great structured guide to the vast literature on ensemble methods

The only other book I know that covers ensemble methods is the well-known "The Elements of Statistical Learning" (TEOSL), which can be quite a dense read at times.For example, TEOSL covers Importance Sampling Learning Ensembles (ISLE) and Rule Ensembles (RE) in a couple of pages each, whereas EMIDM dedicates a chapter to each (personally, I had overlooked the significance of those 2 methods until I read the more developed narrative in EMIDM).

In any event, you should own a copy of TEOSL (which can be freely downloaded off the authors website), but if you want to master ensemble methods (currently one of the hottest areas in data mining and machine learning) and confidently be able to apply them in practice, then EMIDM is a wise investment. ... Read more

Product Description
Kessinger Publishing is the place to find hundreds of thousands of rare and hard-to-find books with something of interest for everyone! ... Read more

Product Description

Most of the research aimed at counterterrorism, fraud detection, or other forensic applications assumes that this is a specialized application domain for mainstream knowledge discovery. Unfortunately, knowledge discovery changes completely when the datasets being used have been manipulated in order to conceal some underlying activity. Knowledge Discovery for Counterterrorism and Law Enforcement operates from the premise that detection algorithms must be rethought to be effective in this domain, and presents a new approach based on cutting-edge analysis for use in adversarial settings.

Reveals How Criminals Conceal Information

This volume focuses on four main forms of knowledge discovery: prediction, clustering, relationship discovery, and textual analysis. For each of these application areas, the author discusses opportunities for concealment that are available to criminals and reveals some of the tactics that can aid in detecting them. He reviews what is known about the different technologies for each area and evaluates their effectiveness. The book also supplies a preview of technologies currently under development and describes how they will fit in to existing approaches to knowledge discovery.

Provides Proactive Formulas for Staying One Step Ahead of Adversaries

While all knowledge-discovery systems are susceptible to manipulation, designers and users of algorithmic systems who are armed with the knowledge of these subversive tactics are better able to create systems to avoid these vulnerabilities. This book delineates an effective process for integrating knowledge-discovery tools, provides a unique understanding of the limits of the technology, and contains a clear presentation of the upsides and pitfalls of data collection. It is a powerful weapon in the arsenal of anyone confronting the increasingly sophisticated tactics employed by lawbreakers and other unsavory individuals.

Product Description
Throughout the nineteenth century, miners were given virtually free rein to profit without having to worry about impacts to the land, water, and air. But during the twentieth century, the mining industry has evidenced serious concerns about its effects on the environment.

Since the 1960s, mining and its consequences have become heated issues of public debate and legislative reform. By the mid-1970s, a number of industry hard-liners were still clinging to nineteenth-century values, but many more were accepting the legacy of mining's past and were beginning to integrate preservation and reclamation into their plans.

Mining America is a vivid account of the damage wrought by almost two centuries of mining, but its main focus is on the conflicting attitudes behind the destruction and on society's responses. Veteran author and historian Duane Smith asserts that the marriage of mining and environmental issues was bound to touch America's sensitive pocketbook nerve — but the question now is, are all groups willing to pay the price? ... Read more

Customer Reviews (1)

Hope Sunrise Gold Rush
"Two years before the famous Klondike gold rush of 1898, hundreds of pioneers & adventurers swarmed to the towns of Hope & Sunrise on Alaska's Kenai Peninsula in one of the littlest-known gold rushes of history. This book traces the story of these hardy pioneers - and others before and after them who perpetrated the eager search for coal, chromite, lime, oil, and of course, gold"

... Read more

Product Description
Managing Data Mining: Advice from Experts is a collection of leading business applications in the data mining and multivariate modeling spectrum provided by experts in the field at leading US corporations. Each contributor provides valued insights as to the importance quantitative modeling provides in helping their corresponding organizations manage risk, increase productivity and drive profits in the market in which they operate. Additionally, the expert contributors address other important areas which are involved in the utilization of data mining and multivariate modeling that include various aspects in the data management spectrum (e.g. data collection, cleansing and general organization).

(This book is a release under the IT Solution Series.)

Foreword by Dr. Jim Goodnight, SAS, Inc., USA

Selected contributions from:

Citigroup Blue Cross Blue Shield Chubb Insurance American Healthways Nielsen//NetRatings ... Read more