Customer Reviews (17)

A wealth of information
The depth and breadth of this guide are downright impressive. The author obviously spent a lot of time exploring Death Valley and this book is one of the most comprehensive guides I have seen to this or any other area. Highly recommended.

Another big thumbs up for this one!
I just wanted to add another 5 star vote for this book: my wife and I spent a week in Death Valley at the beginning of April and this guide was invaluable!

The ultimate guide to Death Valley
While the focus of this book is on hiking, there is so much information on the history, geology, flora and fauna of the region that this served as the primary information source during our visit to Death Valley.Our only regret is that we didn't have far more time to explore.Fortunately, Digonnet's writing style is engaging and lucid enough to allow us to vicariously see areas that we didn't have time to physically visit.

The book eschews several popular road accessible visitor destinations.Most of the roads in the area are treated simply as access routes to the hikes even though there is much to be seen, especially along the 4WD routes.This is not to be taken as a criticism of the author.It simply is not Digonnet's focus.

The book is over 500 pages long.If you are planning your first visit to Death Valley, you would be best served by reading "Part I. A Few Basic Facts" plus the introductions to the remaining eight Parts.With this information you will be able to choose where to begin your exploration.With that settled, read the balance of the Part that covers you selected region and narrow down the trails that you want to travel.Unless you have months of time you will only scratch the surface in one visit.

Wonderful Book!
I have just returned from Death Valley and this book was an excellent resource both before and during my trip.I found the author to be very straight forward about the information presented and very realistic about the wonders and realities of Death Valley.It's a truly amazing place and this book covers an incredible amount of information and detail that will serve me for years to come and many more visits!

Great travel resource
This book is a great resource tool. A fairly inclusive area guide with historical, geological and physical details. More than adequate for most visitors to choose an advanced plan of daily activities. It is not attempting to be a USGS map nor a hikers bible. It is a fairly descriptive summary of things to see, do and where they are.

I purchased this book for helping us plan a 5 day stay in Stove Pipe Wells. Well worth the money spent. ... Read more

Product Description
The recent explosive growth of biological data has lead to a rapid increase in the number of molecular biology databases. Held in many different locations and often using varying interfaces and non-standard data formats, integrating and comparing data from these multiple databases can be difficult and time-consuming. This book provides an overview of the key tools currently available for large-scale comparisons of gene sequences and annotations, focusing on the databases and tools from the University of California, Santa Cruz (UCSC), Ensembl, and the National Centre for Biotechnology Information (NCBI). Written specifically for biology and bioinformatics students and researchers, it aims to give an appreciation for the methods by which the browsers and their databases are constructed, enabling readers to determine which tool is the most appropriate for their requirements. Each chapter contains a summary and exercises to aid understanding and promote effective use of these important tools. ... Read more

Customer Reviews (2)

Fundamental book for Genomics
The UCSC Genome Browser is a powerful tool that provides an open portal to the world's genomic information. But because its so powerful, it is often difficult to use. Here is an authoritative book that will get you on the air, not only with the reference data, but also with the means to compare it with your own data.

This is a terrific book.

powerful analytic tools
The sheer mass of genetic data being assembled by various biotech firms and research labs has led to the rise of genomics. This book describes various computational tools currently available, to help the researcher analyse the data.

One such tool addresses the need to visualise. The brain is best at analysing large amounts of data when presented in visual form. Ensembl and MapViewer are 2 of the so-called genome browsers that have been written. They let you troll thru the data and see it displayed in several ways. While these might be called browsers, they are a far step from the generic web browsers. Be warned that the APIs have very nontrivial learning curves.

Another part of the book looks at querying of databases. Another growing area, with sophisticated needs. ... Read more

Product Description
Solution mining, the extraction of metals, minerals and materials from the earth through leaching and fluid recovery, is still a relatively new but rapidly growing field. The annual economic value of solution mined metals in the United States now exceeds that of metals extracted by underground mining.
Originally published in 1992, this second edition of an introductory text for students and professional engineers expands information on the science of fluid flow in heaps, nonsteady state in situ fluid flow and nonsteady state well hydraulics. Information on bioheap pretreatment of refractory gold ores and the environmental stabilization of contaminated earth materials has been added. ... Read more

Customer Reviews (2)

heap leaching
This book has a lot of useful information about the heap leaching, that is theoretical information and real data from field.

For me is one of the best books about heap leaching.

Dr. Bartlett really enhanced the second edition, WOW.
This is a very readable intro to how mining is done today, and can be the best book you'll ever read if you are an operator or consultant in mining, environmental remediation... Dr Bartlett knows his stuff and has theexperience in industry to back up his writing. Especially valuable are theend-of-chapter problems which were really well-done and amended from 1stedition. Work a few problems to appreciate the power of the book. ... Read more

Product Description
Making obscure knowledge about matrix decompositions widely available, Understanding Complex Datasets: Data Mining with Matrix Decompositions discusses the most common matrix decompositions and shows how they can be used to analyze large datasets in a broad range of application areas. Without having to understand every mathematical detail, the book helps you determine which matrix is appropriate for your dataset and what the results mean.

Explaining the effectiveness of matrices as data analysis tools, the book illustrates the ability of matrix decompositions to provide more powerful analyses and to produce cleaner data than more mainstream techniques. The author explores the deep connections between matrix decompositions and structures within graphs, relating the PageRank algorithm of Google's search engine to singular value decomposition. He also covers dimensionality reduction, collaborative filtering, clustering, and spectral analysis. With numerous figures and examples, the book shows how matrix decompositions can be used to find documents on the Internet, look for deeply buried mineral deposits without drilling, explore the structure of proteins, detect suspicious emails or cell phone calls, and more.

Concentrating on data mining mechanics and applications, this resource helps you model large, complex datasets and investigate connections between standard data mining techniques and matrix decompositions. ... Read more

Customer Reviews (1)

Comprehensive and well-written!
I am doing research in data mining using tensor decompositions, and was very impressed by this book. It not only covers all of the important matrix and tensor decompositions, but also methods for computing them (with Matlab code!), the computational complexity of these methods, the tradeoffs and scenarios associated with each decomposition, and potential areas of application. To top it all off, the book is written in a highly approachable manner, covering the general concept of a decomposition and gradually discussing the specific decompositions from simplest to most complex. Highly recommended. ... Read more

Product Description
This volume is produced from digital images created through the University of Michigan University Library's large-scale digitization efforts. The Library seeks to preserve the intellectual content of items in a manner that facilitates and promotes a variety of uses. The digital reformatting process results in an electronic version of the original text that can be both accessed online and used to create new print copies. The Library also understands and values the usefulness of print and makes reprints available to the public whenever possible. This book and hundreds of thousands of others can be found in the HathiTrust, an archive of the digitized collections of many great research libraries. For access to the University of Michigan Library's digital collections, please see http://www.lib.umich.edu and for information about the HathiTrust, please visit http://www.hathitrust.org ... Read more

Product Description
Underground Mining Methods presents the latest principles and techniques in use today. Reflecting the international and diverse nature of the industry, a series of mining case studies is presented covering the commodity range from iron ore to diamonds extracted by operations located in all corners of the world. Industry experts have contributed 77 chapters. This book is certain to become a standard for every practicing mining engineer and student alike. Sections include: General Mine Design Considerations, Room-and-Pillar Mining of Hard Rock/Soft Rock, Longwall Mining of Hard Rock, Shrinkage Stoping, Sublevel Stoping, Cut-and-Fill Mining, Sublevel Caving, Panel Caving, Foundations for Design, and Underground Mining Looks to the Future. ... Read more

Customer Reviews (1)

From IJSMVol 15, No 4 December2001
Beginning with the Phoenician traders more than 3000 years ago, mining today is an international business.This book has tried to reflect this international character by presenting a snapshot of the world of mining through a series of case studies.The publication is devoted strictly to underground mining and can be used for the training of new mining engineers as well as a reference book for those already in the field. The case studies in this book cover the commodity range from iron ore to diamonds extracted by operations located in all corners of the world.The book consists of 11 sections making up 77 chapters.The sections are entitled as follows:General Mine Design Considerations; Room-and-Pillar Mining of Hard Rock Room-and-Pillar Mining of Soft Rock; Longwall Mining of Hard Rock; Shrinkage Stopping; Sublevel Stoping Cut-and-Fill Mining; Sublevel Caving; Panel Caving; Foundations for Design; and Underground Mining Looks to the Future.Black and white visuals are presented throughout the book and a comprehensive topic index is provided ... Read more

Product Description
This 800+ page book contains a wealth of information for mining students and industry professionals. It consists of selected material from the out-of-print industry standard, Underground Mining Methods Handbook. More than 40 chapters covering such underground mining topics as sampling, planning, reserve analysis, cost calculations, various methods of support, block and panel caving, and sublevel caving make up this comprehensive text. Numerous tables and figures enhance the extensive material found in each chapter. An excellent teaching tool and source book, Techniques in Underground Mining is a must for any mining student or engineer. ... Read more

Customer Reviews (2)

A reviewed selection of a must-have handbook
For those which on 1982 were too little to study or work with the original blue book, this handbook is a valuable selection of the topics covered in that handbook which are in some parts updated. I think it's a very good reference book for mining engineers, hoping that the new comprehensive version of the blue book will be available soon.

Underground Mining: A full review
This textbook is a longer review about all the types of underground mining, based in real applications in mining operations around the world. It's an excellent text for mining engineering students or people that work in related companies. ... Read more

Product Description

This book offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining-including both tried-and-true techniques of the past and Java-based methods at the leading edge of contemporary research. If you're involved at any level in the work of extracting usable knowledge from large collections of data, this clearly written and effectively illustrated book will prove an invaluable resource.

Topics covered: Data mining and machine learning basics, sample datasets and applications for data mining, machine learning vs. statistics, the ethics of data mining, generalization, concepts, attributes, missing values, decision tables and trees, classification rules, association rules, exceptions, numeric prediction, clustering, algorithms and implementations in Java, inferring rules, statistical modeling, covering algorithms, linear models, support vector machines, instance-based learning, credibility, cross-validation, probability, costs (lift charts and ROC curves), selecting attributes, data cleansing, combining multiple models (bagging, boosting, and stacking), Weka (reusable Java classes for machine learning), customizing Weka, visualizing machine learning, working with massive datasets, text mining, and e-mail and the Internet. ... Read more

Customer Reviews (17)

An Excellent Data Mining Text
This book covers data mining at a serious level, including essential material on testing and a broad array of techniques.It is written for practitioners and provides clear explanation of included topics.Easily one of the best 5 books on data mining currently available.

Note that this book has moved on to a second edition.

A good book to practice
I have bought this book as course book to learn some particular aspects of data mining.
With the software that you can dowload you can do yourself all the exercices for every models presented
It's the best way to progress
Do the same, it's simple and funny
The explanations are very clear and pedagogical, very practical

A nice complement to the other data mining bible
Witten's book, combined with the accompanying open source package, Weka, provides a great overview of data mining principles and practice from a machine learning perspective. One could hardly do better than to own this book and "The Elements of Statistical Learning; Data Mining, Inference, and Prediction" by Hastie, Tibshirani, and Friedman which covers complimentary material from the statistician's perspective. Witten does an amazing job of providing a comprehensive overview of the field while still providing some depth re. the algorithms; after reading the book I didn't feel like I'd read yet another large volume of empty claims about the power of information technology to make me rich and famous. In fact, with the book by my side, in a relatively short time I was able to use Weka to pry some useful information from one of my medical imaging data sets (maybe even enough to serve as preliminary data for a grant application). It seems to me that with an understanding of the material in this book and the one by Hastie et. al. one could embark on serious data mining projects.

Stop searching for datamining: You've found it.
I've been working with "big name software" for some years, but when I joined the institution I work now and no tools where available I begun my quest for an open source tool that could help me build statistical models applied to real business problems.

As a result of this quest I found the WEKA data mining software on the Internet (you can find it on www.cs.waikato.ac.nz/~ml/weka/) and that nice piece of software leaded me to this book.

This book is EXCELLENT and I am giving 5 *five* stars to it as it helped me understanding the whole process of datamining: from loading the data to building the model.

I've read some reviews and I think some of them are not fair (particularly one that says that this book have "just words with no relation or sense at all").. THIS BOOK IS REALLY WELL WRITTEN but you have to read it slowly: As when you study something.

Buy this book (*don't forget to download the software*) and I am totally sure that you will be producing and using models in a week.

Can't imagine that some weeks ago

Cheers,

Try to cover many, but not depth enough.
This book is actual a textbook for a data analysis course. We use it because the flow of the chapters is almost the same as the flow of the course material. Unfortunately, it is not as useful as expected if you are in the field. It is not in depth for the materials that the authors wanted to cover due to the fact that this is not a book for just programming or just statistics. If you have a strong background on machine language or a strong background on data analysis, you may not find it useful for you career. This book is for those who have limited knowledge on both programming and statistics, but not for professionals. ... Read more

Product Description

This book is not just another theoretical text about statistics or data mining. No, instead it is aimed for you DBAs who want to use SQL, or bolster your understanding of statistics to support data mining and customer relationship management analytics.

Each chapter is self-contained, with examples tailored to real business applications. And each analysis technique will be expressed in a mathematical format for coding as either a database query or a VB procedure using SQL. Chapter contents include formulas, graphs, charts, tables, data mining techniques, and more!Amazon.com Review
Data Mining and Statistical Analysis Using SQL concerns itself with the interface between applied mathematics--the discipline of statistical analysis--and really applied mathematics in the form of Structured Query Language (SQL) code that carries out such analysis. It's a subject that deserves careful coverage in a book, and the authors of this one--both working analysts with distinguished academic backgrounds--have done great work. If you're faced with a need to derive meaning from large quantities of data (from retail sales, industrial processes, or even scientific observations), and canned analysis tools aren't cutting it for you, take time to study what Robert Trueblood and John Lovett have to say.

Though some background in statistics will help you pick up on what Trueblood and Lovett have written, a low-level university class (even one far in your past) should be enough. Their approach to all of the analysis techniques they teach is to explain terms and concepts with prose, then with graphs, then with formulas. Then, they translate the formulas into SQL queries for Microsoft Access and show variations on the code that yield differently tweaked results. Finally, T-SQL source code (for Microsoft SQL Server 2000) is listed, though most readers will prefer to grab this code from the book's companion Web site. Additional coverage of graphics would make this book better, but in its present state it's great reading for people who want to interpret their mountains of data. --David Wall

Topics covered: Statistical analysis as a set of mathematical tools that may be implemented in Structured Query Language (SQL), specifically SQL variants for Microsoft database products. Chapters explain how to use hypothesis testing, curve fitting, scatter plots, measurements of central tendency, and regression analysis to spot significant characteristics of data. ... Read more

Customer Reviews (6)

Strange Collection of Summary Statistics in SQL
This book is not about data mining at all, but implementing an unusual collection of summary statistical procedures in SQL.For those interested in data mining, get a book on data mining using actual data mining tools.

Liar, liar, pants on fire--no data mining in this book
This is yet another introductory statistics text--a particularly old-fashioned one.The words "Data Mining" in the title are toitally misleading and I'm sorry I borrowed it. It is useless as a text book as it has nothing on resampling methods, the bootstrap and permutation tests.

Should be called "Basic Statistical Analysis Using SQL"
My perspective is that I do not consider basic statistics a part of Data Mining. By basic statistics, I mean ANOVA, regression, etc. Therefore, I feel the title is misleading. Only basic statistical analysis is shown using SQL. Data Mining techniques are not covered.

As far as statistical analysis .... The Design of Experiments chapter does not cover replicated ANOVA, and does not even mention factorial designs. The Time Series chapter does not cover autoregressive-moving average models.

If you want a book that implements some of Excel's Analysis Tools routines in SQL, then this book is for you. If you want an introduction to data mining techniques, look elsewhere.

A Must Read for all database administrators !
It might not be the perfect data mining book as the other reviewer has stated in his or her review. However, it is packed with plenty of useful examples and techniques, carefully marked with detail explanations. This is not a bad sort at all amongst the SQL books. Not bad at all. Ya just gonna have to get ya butt out and walk yaself to a good book store and read it yaself if ya don't believe me. Or, you can just keep sitting there and keep browsing the net to find that one perfect SQL book that's suitable for you.

A Must Read for all database administrators !
It might not be the perfect data mining book as the other reviewer has stated in his or her review. However, it is packed with plenty of useful examples and techniques, carefully marked with detail explanations. This is not a bad sort at all amongst the SQL books. Not bad at all. Ya just gonna have to get ya butt out and walk yaself to a good book store and read it yaself if ya don't believe me. Or, you can just keep sitting there and keep browsing the net to find that one perfect SQL book that's suitable for you. ... Read more

Product Description

This book is a thorough introduction to the most important topics in data mining and machine learning. It begins with a detailed review of classical function estimation and proceeds with chapters on nonlinear regression, classification, and ensemble methods. The final chapters focus on clustering, dimension reduction, variable selection, and multiple comparisons. All these topics have undergone extraordinarily rapid development in recent years and this treatment offers a modern perspective emphasizing the most recent contributions. The presentation of foundational results is detailed and includes many accessible proofs not readily available outside original sources. While the orientation is conceptual and theoretical, the main points are regularly reinforced by computational comparisons.

Intended primarily as a graduate level textbook for statistics, computer science, and electrical engineering students, this book assumes only a strong foundation in undergraduate statistics and mathematics, and facility with using R packages. The text has a wide variety of problems, many of an exploratory nature. There are numerous computed examples, complete with code, so that further computations can be carried out readily. The book also serves as a handbook for researchers who want a conceptual overview of the central topics in data mining and machine learning.

Product Description
Learn Data Mining by doing data mining
Data mining can be revolutionary-but only when it's done right. The powerful black box data mining software now available can produce disastrously misleading results unless applied by a skilled and knowledgeable analyst. Discovering Knowledge in Data: An Introduction to Data Mining provides both the practical experience and the theoretical insight needed to reveal valuable information hidden in large data sets.
Employing a "white box" methodology and with real-world case studies, this step-by-step guide walks readers through the various algorithms and statistical structures that underlie the software and presents examples of their operation on actual large data sets. Principal topics include:
* Data preprocessing and classification
* Exploratory analysis
* Decision trees
* Neural and Kohonen networks
* Hierarchical and k-means clustering
* Association rules
* Model evaluation techniques
Complete with scores of screenshots and diagrams to encourage graphical learning, Discovering Knowledge in Data: An Introduction to Data Mining gives students in Business, Computer Science, and Statistics as well as professionals in the field the power to turn any data warehouse into actionable knowledge.

An Instructor's Manual presenting detailed solutions to all the problems in the book is available online. ... Read more

Customer Reviews (2)

One of the best explanations of Decision Trees to be found
There is a lot to like about this book, but it has some unfortunate flaws. Note that it is part of a Data Mining trilogy. The other two books are: Data Mining Methods and Models and Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage.

My initial reaction was more negative as I feel strongly about the issues that this book addresses poorly. However, I find myself turning to this book again and again. I would endorse it highly, but with a caution or two. The very best features of the book are the exceptionally clear explanations of complicated algorithms. In particular, Chapters 6 and 7 and their explanations of Decision Trees and Neural Nets are just perfect for both new and veteran analysts who want to understand what is happening "under the hood". Those chapters are stand-outs, but all of the 80%+ part of the book that describes algorithms in detail (clear, careful, and readable detail) is uniformly excellent. For some readers, it may be the first time that the techniques really make sense to them.

Now the flaws. The three book format is, frankly, annoying. The second book and third books are much weaker, but the it was clearly designed as a trilogy, so it is hard to recommend the first to a client without at least implicitly recommending the second. Spending my reading time well is more important to me than my reading budget, but the set of three costs more than $200. Unless you plan on an entire shelf of related books, like me, I can't recommend the entire set.

The other flaw is less obvious, and is the one that concerns me the most. Although this book cites Dorian Pyle's excellent book ... it seems to miss the whole point. Data Mining data prep is quite different from data prep for statistics. Although the two areas share a lot in common, and while mastery of statistics is a good thing for data miners, this is one of the differences between the two disciplines. Data cleaning and data reduction are critical, but this book suggests that this is accomplished by the human doing all possible bivariates. Recommendations of factor analysis and log transformations abound, but never with cautions of when that is unnecessary or even a bad idea - something Pyle's book explores. Also, transformations like binning come off as something the analyst does during data exploration, getting it perfect before modeling. Sounds like statistics data prep to me - not data mining data prep. If anyone has ever completed data prep without preliminary modeling, or has modeled without having to revisit data prep, I have never heard of it. If a novice data miner were to take the advice too literally, they could get themselves into trouble. This would be especially true of a reader that is well versed in statistics - there is a predictable set of mistakes awaiting the classically trained on their first data mining project!

My advice? There is a lot to benefit from here. All of the "white box" walk through examples are great. Consider buying this book, the Pyle book Data Preparation for Data Mining (The Morgan Kaufmann Series in Data Management Systems), and Berry and Linoff Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management, while skipping the other two in this trilogy. Use this book for the algorithm explanations, but be cautious otherwise.

The screen shots and discussion of Clementine may be helpful to you, but note that Clementine 8.5 was used.

conveys basic ideas
The book gives a good introduction to data mining. Larose manages to cover the important techniques used to analyse data and turn it into knowledge. These include neural networks, various types of clustering. Most importantly, perhaps, he discusses how to try various models and how to evaluate the effectiveness of each model.

The book's length is insufficient for many readers to actually get enough information to apply several of the methods. The details of using neural networks, for example, can be quite voluminous. But the value of the book is in conveying the basic qualitative ideas of the methods. ... Read more

Product Description
Mining Group Gold is a book on leadership. It explores the process of managing people and ideas to achieve a high level of results in a complex, turbulent global economy. This book is a practical, easy to use guide to building and maintaining collaboration within and across teams.

Includes:

• Five steps for planning and conducting a successful group session
• Suggestions for dealing with feelings and emotions, as well as conflict and confusion, during a session

Options for enhancing the productivity of the middle of a meeting ... Read more

Customer Reviews (7)

Powerful for professional and personal life
Reading Mining Group Gold was part of our Toolbox at the beginning of our MBA program at Hult IBS. The book gives great inside to the power of team work. It provides tools for various situations and problems that might occur when working in a team. Different roles of team members are getting defined and common traps are described.

The book provides powerful insights to managers, students and people that are organized in team and group work. Especially for people that facilitate teams, Mining Group Gold is a great resource for discovering hidden traps and common obstacles. It leads the reader to the knowledge of the great performance that teams can achieve, if they are formed well and roles are defined and structured. For the process of forming and structuring of teams, Mining Group Gold offers tips and tools and provides the reader with helpful thoughts.

Golden Ideas for Mining Gold from Your Groups
This is really as much a book about effective leadership and management as it is about group facilitation. Solidly grounded in the author's experience at Xerox, it teaches everything needed to make your group sessions far more effective than it currently is. It also includes guidesheets, tables and surveys that you will find useful in planning, facilitating and evaluating your sessions.

Mining Group Gold
I read Tom Kayser's book in the early 1990's when it was originally written for Xerox.The new edition is a fine adaptation.The book has been immensely helpful to me as a facilitator.It gives great instructions to a new and experienced group leader.

Mr. Kayser understands group dynamics.By reading and more importantly, following his "recipes", you will find that meetings are both more efficient and effective.

Treasure Trove of Productivity
One of the most valuable lessons I learned in my brief time as a researcher at the Xerox Palo Alto Research Center was that meetings need not be unending wastes of times. When I first noticed this and asked how itwas possible that so much always seemed to get done, no mater who wasinvolved, I was given a copy of the Tom Kayser book "Mining GroupGold".

What a wonderful and unexpected surprise reading it was!Although concrete steps are given to guide people into getting the most outof working together and, more important, thinking together, its basic valuecomes from the way it enables folks to remain themselves - only do a betterjob of it.

Since leaving Xerox three years ago to be a consultant forMicrosoft, General Electric and Sun Microsystems, I've given numerouscopies to new cohorts so as to make life easier and the flow of work moreefficient for all.

Tap the Mother Lode of Collaborative Cranial Creativity
Thomas A. Kayser has set forth a systematic means for gaining the maximum benefit from meetings.

Starting with John Kenneth Gailbraith's infamous attribilious amphigory: "Meetings are vital to those who want to makesure nothing happens" Kayser leads the reader through the labyrinth oftraditional meeting quagmires and enables everyone to profit from combiningtheir brain power optimally.

In practical, no-nonsense terms, nothing isleft to chance. Those who practice the lessons will reap the immediate andcontinued rewards from the old axiom of time being money! ... Read more

Product Description
While it has become increasingly commonplace to speak of how history books omit the stories of people of color, rarely is the discussion broad enough to examine how these same omissions are replicated in institutions outside the academy. One such institution is the museum, particularly the history museum, which, much like a history book, is popularly perceived as a repository of truth. But as Mining the Museum, a book based on the award-winning collaboration between The Contemporary, The Maryland Historical Society, and installation artist Fred Wilson illustrates, museums are not neutral places. ... Read more

Customer Reviews (1)

Wow !!!!!!!!
It is a clever and very well done book about The Mining the Museum exhibition. On reading it we can revival the experience of beeing in the show again...so many graphic solutions and details... ... Read more

Product Description

Leverage Unstructured Data to Become More Competitive, Responsive, and Innovative

In Mining the Talk, two leading-edge IBM researchers introduce a revolutionary new approach to unlocking the business value hidden in virtually any form of unstructured data–from word processing documents to websites, emails to instant messages.

The authors review the business drivers that have made unstructured data so important–and explain why conventional methods for working with it are inadequate. Then, writing for business professionals–not just data mining specialists–they walk step-by-step through exploring your unstructured data, understanding it, and analyzing it effectively.

Next, you’ll put IBM’s techniques to work in five key areas: learning from your customer interactions; hearing the voices of customers when they’re not talking to you; discovering the “collective consciousness” of your own organization; enhancing innovation; and spotting emerging trends. Whatever your organization, Mining the Talk offers you breakthrough opportunities to become more responsive, agile, and competitive.

• Identify your key information sources and what can be learned about them
• Discover the underlying structure inherent in your unstructured information
• Create flexible models that capture both domain knowledge and business objectives
• Create visual taxonomies: “pictures” of your data and its key interrelationships
• Combine structured and unstructured information to reveal hidden trends, patterns, and relationships
• Gain insights from “informal talk” by customers and employees
• Systematically leverage knowledge from technical literature, patents, and the Web
• Establish a sustainable process for creating continuing business value from unstructured data

Preface xv

Acknowledgements xx

Chapter 1: Introduction 1

Chapter 2: Mining Customer Interactions 21

Chapter 3: Mining the Voice of the Customer 71

Chapter 4: Mining the Voice of the Employee 93

Chapter 5: Mining to Improve Innovation 111

Chapter 6: Mining to See the Future 133

Chapter 7: Future Applications 163

Appendix: The IBM Unstructured Information Modeler Users Manual 171

Customer Reviews (15)

Excellent & approachable text-mining book
Spangler and Kreulen have both been working in this field for some time, and they've created a book that provides a very readable introduction to the field (even for nonspecialists), along with helpful and practical examples.

Valuable Source
The authors have done an excellent job of addressing a common problem.That is, getting useful information from disorganized sources.The problem and the solution offered are presented in a clear and easily read form.The information presented will be valuable to any organization that needs to know more about the opinions of their customers and employees, and of course that is any organization.

Highly Readable and Intriguing
The authors present a highly readable account of how value can be obtained from unstructured data.The organization of the book makes it easy to follow, as each chapter seems to build upon the previous ones, yet provides new insights. The culmination, with Mining to See the Future, leaves the reader with thought provoking ideas and a desire to try the provided software referenced. I recommend this book to anyone interested in statistical problem solving and future trends in language understanding.

Finding the real value in your unstructured data...
So how many of you IT professionals have faced this particular question from someone in your IT organization?"We have so much data locked up in (email/forums/wikis/etc.), and we can't analyze it".

Thought so...

I had the opportunity to read and review the book Mining the Talk: Unlocking the Business Value in Unstructured Information, and I think it's one of those books that can change the way your organization views this type of data.

Table of Contents:
1. Introduction
2. Mining Customer Interactions
3. Mining the Voice of the Customer
4. Mining to Improve Innovation
5. Mining to See the Future
6. Future Applications
7. The IBM Unstructured Information Modeler Users Manual
Index

Spangler and Kreulen are IBMers who have spent a lot of time working with the concepts behind mining data that resides in unstructured formats.This could be web pages, help desk tickets, discussion database, or what have you.Once you step outside the structured world of relational databases and official taxonomies, it's often thought that the only way to get a feel for what's happening is to have someone responsible for reading it all.But there *is* a better way...

Using a tool named The IBM Unstructured Information Modeler, they show how you can use software to analyze unformatted data, cluster the results and keywords, and develop a real taxonomy that covers what is truly happening in your business.For instance, your help desk system probably has categorization fields.But you'll never get all the combinations that could happen, nor will every last help desk person categorize things in the same way.Using this tool, you can pass in the unstructured data (comment fields) and start to get a feel for what really is happening.Then by refining and grouping the initial results, the taxonomy for the target data can be accurately grouped for even larger datasets.The net result is a true view into what issues are occurring most often, in what combinations, as well as where most of the issues come from.These combinations might remain hidden if you rely on typical structured reporting based on static categorization.But with a little effort, you can start to gain insights not readily available by other means.

Even better...There's a version of the software tool that is downloadable from the AlphaWorks site, so you can start experimenting with your own data mining efforts.The install is straight-forward and easy, so it's not as if you'll spend two days trying to get a proof-of-concept going.You could easily pull off an initial test in a couple of hours, and then use that to decide if you need to expand your efforts to a larger dataset and the licensed version of the software.

Think of what this means for all your discussion and document databases out there.No longer would you need to "apologize" for not having the capabilities to analyze and mine the information stored out there.A 15 minute rollout of a discussion database can start paying immediate communication dividends, and then the mining tool could be used to spot trends and hot points.That's some powerful abilities coupled with immediate ROI to the business.Can't beat that combination...

It's well worth the time to pick up a copy of this book and try out the mining software.You might even want to run it against your mail file to see where and who is taking most of *your* time and attention.

Mining the Talk - and explaining it to non-IT professionals
The authors have created a highly readable, yet technically comprehensive, work about a topic of critical importance in the current marketplace.As an IT professional frequently faced with convincing non-IT colleagues of the importance of technology in industry, this book is just the kind of tool needed. It presents a solution that is ingenious and innovative, and has direct practical application to current business problems. I can think of many immediate uses in my industry and the straightforward presentation, with clear examples, practically sells the concept of mining unstructured data by itself.It makes the job of communicating important, complex concepts to decision-makers who often have no IT background almost easy!Especially for large to medium-sized corporations struggling with basic data management, and missing huge opportunities for discovering the value hidden in their data, this book will be enormously important.

Linda J. Joseph, PhD
ME Technology
General Motors Corporation ... Read more

Product Description
Publisher: London, C. Griffin ... Read more

Product Description
Mining, as one of the world's earliest industrial activities, continues to yield minerals and resources both valuable and fundamental to civilization. Yet the industry that produces such riches is not as lucrative as it may seem. It is one endeavor to discover a mineral deposit, and quite another to mine it profitably.

The industry's strategy for coping with low profitability has focused primarily on controlling production costs. Despite mechanization, automation, and other technical improvements, the aggregate profitability of mining still falls far short of that realized by most other industries.What appears to be lacking, contends author Juan Camus, is not additional technical knowledge, but rather sound management practices that utilitize the existing knowledge base more productively. Management of Mineral Resources aims to raise the level of mining profitability through better management--the process of generating plans and supervising their implementation.

This book is concerned with the analysis of some of the internal, controllable factors that influence mining production effectiveness. It combines the best thinking in mining and management so that practitioners can devise a concrete strategy for generating maximum shareholder value. Ideas in both of these areas have rapidly evolved in recent years, and this insightful text presents an authoritative review of the current state of the art.

A mass of published material exists, yet it is widely scattered--much of it in technical papers--and therefore not readily accessible. The thought-provoking material in this book has been selected, summarized, and presented by the author in a form that preserves the perspective of its relative importance. ... Read more

Customer Reviews (1)

Principles to Create Huge Value from Mineral Resources
"...the main question for the company is whether to exploit, sell, or hold the deposit for future use. Mineral resource management can be seen as the discipline that deals with the required activities to support and make this decision."

This book explains the why, how and who of this fundamental decision faced by mining companies. The author also explains why this should be of vital interest to governments, educational institutions and the struggling shareholders of mining companies. Consequently, this book should be in the hands of anyone involved in, or aspiring to, management at either the operating or corporate level of the minerals industry.

Juan P. Camus explains in plain language the theory and use of cutoff grade optimization techniques developed by people such as Kenneth F. Lane, author of the highly regarded book, "The Economic Definition of Ore". The foreword is written by Ken Lane, who lays a challenge for the next book on this fascinating and fundamental aspect of our industry.

The real-life examples, based upon Juan's personal experience, illustrate how these optimization tools helped create huge value from mineral resources. Following the successful application of these principles of optimization within Codelco, the CEO of the world's largest copper producer is quoted as saying, "In the past, we were doing things right, but it seems that now we are doing the right things." These "right things" contributed well over a billion dollars to Codelco's value and still hundreds of millions more for another large Chilean copper producer. Interestingly, the author points out that the techniques he advocates could apply in other industries.

However, beyond the tools and of at least equal importance, the author reviews organizational theory to propose structures and systems to capture opportunities for value creation, which he contends elude too many players in the mining industry. The author distinguishes between Strategic and Tactical mine planning stages, noting their different objectives, roles, time horizons, technical requirements, the types of people suited to each and their relative value creation potential. The author argues that without the proper systems in place for planning, the value of the mineral resource will be sub-optimal. Not only will the owners' be worse off as a consequence, but so also will governments, suppliers and society at large. Proper management of resources is vital to the mineral industry.

The book can be read relatively quickly, touches upon a wide breadth of knowledge and will leave the reader realizing that value creation in the mineral industry goes well beyond the familiar routines of employing economy of scale and cutting costs. As the author amply illustrates, the value of mineral resources lies very much in the application of intellect and ingenuity. ... Read more

Product Description
Clinical Data-Mining (CDM) involves the conceptualization, extraction, analysis, and interpretation of available clinical data for practice knowledge-building, clinical decision-making and practitioner reflection.Depending upon the type of data mined, CDM can be qualitative or quantitative; it is generally retrospective, but may be meaningfully combined with original data collection.

Any research method that relies on the contents of case records or information systems data inevitably has limitations, but with proper safeguards these can be minimized.Among CDM's strengths however, are that it is unobtrusive, inexpensive, presents little risk to research subjects, and is ethically compatible with practitioner value commitments.When conducted by practitioners, CDM yields conceptual as well as data-driven insight into their own practice- and program-generated questions.
This pocket guide, from a seasoned practice-based researcher, covers all the basics of conducting practitioner-initiated CDM studies or CDM doctoral dissertations, drawing extensively on published CDM studies and completed CDM dissertations from multiple social work settings in the United States, Australia, Israel, Hong Kong and the United Kingdom. In addition, it describes consulting principles for researchers interested in forging collaborative university-agency CDM partnerships, making it a practical tool for novice practitioner-researchers and veteran academic-researchers alike.

As such, this book is an exceptional guide both for professionals conducting practice-based research as well as for social work faculty seeking an evidence-informed approach to practice-research integration. ... Read more

Customer Reviews (13)

From Data Mining to Meaning Creation
"With Clinical Data-Mining: Integrating Practice and Research, Irwin Epstein does something unique and wonderful in social work research: he tells a story.In doing so, he opens a door for a distinct approach to the production of knowledge.While much of agency research is divided from practice, Epstein makes a case for integrating the two by doing something as simple as taking a second look at intake, assessment, and service utilization reports long entered and filed away. Important data can be found from this material. Meaning can be gleamed if one asks the right questions.By connecting an unobtrusive research method with the most basic of agency practice of data collection, Epstein offers an ethical framework for the generation of new knowledge to improve our understanding of both ourselves and the work we do.

Benjamin Shepard, PhD,Assisant Professor of Human Services, City Tech/ City University of New York

A good guide if you want to study your own work
This is a good and quite easy book to read (even for those who don't have english as our first language)if you want to study your own work or do a practice based master or doctorate thesis. It's obvious that Epstein has a lot of experience in the research field and in this method. He is very critical of evidence-based practice and a lot of pages are full of this critisism which is quite unecessary and doesn't add anything to the book.

Delightful!
As someone who has struggled teaching research to social work students for many years, I found this pocket guide a delightful addition to the literature!As other readers have said, it is clear and easy to read.It is of special value to those in social work practice (and other practice fields) who are interested in answering practical research questions in the real world.Using examples from practice research (both quantitative and qualitative)Epstein illustrates a method that will be of value to practitioners and doctoral students alike.It also makes an important contribution to the field which is struggling with pressure to incorporate evidence-based practice.Epstein's story on the "gold standard" is worth the price of the book! Reading this book is like having lunch with a friendly, funny guy who has tons of practical experience and is willing to share it with you.How great is that?!?

Clinical DataMining
I was heartened in reading Irwin Epstein's book. He is one of the few academicians who has been making research real for years. His concept of clinical datamining allows researchers to do more with less and relate the research to real, naturally-existing data. If only more researchers and funders would read his book, we might get more usable and less costly lessons from research.

Bill Cabin, PhD, JD, MSW

A Student's Perspective on Clinical Data-Mining
Clear, objective and most importantly accessible -- Epstein's Clinical Data-Mining:Integrating Practice and Research offers practitioner-researchers with a perspective on and rationale for the use of this methodology.Written for social workers, this book explains what CDM is and where it sits among methodological choices.Would you like to know whether and how to make the case for CDM in your dissertation?It's in here.Are you a practitioner with access to data who wants to use that data to make the case for practice or policy?You too will want to check this book out!CDM is not a magic bullet for the anxious doctoral candidate or practice-researcher -- to do it and do it well requires time and effort.The book explains that too.

Throughout, Epstein's irreverence, humility and candor invites students and practitioners to consider CDM as a way to integrate their practice knowledge with research aspirations. As a student who is planning a CDM study, I welcomed the frank tone and exposition.Best of all are the detailed anecdotes from those who have used CDM, completed their doctoral dissertations and survived -- enough so that they have gone on to illustrious careers.From beginning to end, this book encourages practice-based research yet it also takes a decided student- and practitioner-centered approach in its exposition and presentation of content.This book **motivates** doctoral students and practitioners to do research.Doctoral candidates will read this and see your way to "pay dirt" (meaning completion, sadly not $$ for us social workers!).
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