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
This is an EXACT reproduction of a book published before 1923. This IS NOT an OCR'd book with strange characters, introduced typographical errors, and jumbled words.This book may have occasional imperfections such as missing or blurred pages, poor pictures, errant marks, etc. that were either part of the original artifact, or were introduced by the scanning process. We believe this work is culturally important, and despite the imperfections, have elected to bring it back into print as part of our continuing commitment to the preservation of printed works worldwide. We appreciate your understanding of the imperfections in the preservation process, and hope you enjoy this valuable book. ... 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
Business Modeling and Data Mining demonstrates how real world business problems can be formulated so that data mining can answer them. The concepts and techniques presented in this book are the essential building blocks in understanding what models are and how they can be used practically to reveal hidden assumptions and needs, determine problems, discover data, determine costs, and explore the whole domain of the problem.

This book articulately explains how to understand both the strategic and tactical aspects of any business problem, identify where the key leverage points are and determine where quantitative techniques of analysis -- such as data mining -- can yield most benefit. It addresses techniques for discovering how to turn colloquial expression and vague descriptions of a business problem first into qualitative models and then into well-defined quantitative models (using data mining) that can then be used to find a solution. The book completes the process by illustrating how these findings from data mining can be turned into strategic or tactical implementations.

· Teaches how to discover, construct and refine models that are useful in business situations
· Teaches how to design, discover and develop the data necessary for mining
· Provides a practical approach to mining data for all business situations
· Provides a comprehensive, easy-to-use, fully interactive methodology for building models and mining data
· Provides pointers to supplemental online resources, including a downloadable version of the methodology and software tools. ... Read more

Customer Reviews (4)

Great book
Business Modelling and Data Mining is an extremely clear and didactic work that explains and exemplifies business-oriented data analysis.
Its structure goes fromgeneral to particular, from theory to practice. It is a work about concepts and its applications.
In the so complex, uncertain and fast world of today, those is charge of making decisions in business need to discover which useful information is contained in their data bases to be able to take the necessary measures tending to achieve competitive advantages. This work explains how to be successful in that direction, integrating qualitative and quantitative analysis of concepts.
Dr. Pyle's added value is linking data mining to business. The reader with a previous knowledge ofdata mining will be able to understand its useful application in the world of business. The one already familiar with business will learn about new technologies to improve tactic and strategic decision-making.
It is evident from my words that I do not agree with Alphonse LaTuune's vision, who I think has misinterpreted this book's purpose. Whereas detailed explanations on how to work with data mining algorithms are not necessary,it is important to highlight how to add value to decisions in business. The latter is, definitely, Business Intelligence.
Whether you want to initiate learning, or deepen your understanding of the subject, do not hesitate to read this book. You will not regret it.

Not a _practical_ introduction
I selected Pyle's book, sight unseen, as an introduction for undergraduate students in an information science curriculum.A third the way through the course students are beginning to ask "where's the beef?", and understandably so.Even a business reader in search of an overview of the topic will likely find this discussion weighted with waffling wordiness.

The author devotes page after page to talking about models and mining in a style that is somehow both wordy and imprecise.A reader who is interested in the author's feelings about modeling and mining might find it illuminating; students who are interested in learning how it works and how to _do_ it find it unsatisfying.

I recommend the next edition edit the first 300 pages or so down to 30, and devote the word-count more to real life examples, specific mathematical explanations, and practical exercises.

Wonderful Book
The translation of the business problem into a Data Mining problem is the key for successful data mining projects. Mr Pyle's book deals with this subject in a remarkable way. The book is organized in four parts. The first part provides an introductory material. It shows a broad view of the modelling and mining. This part allowed me to grasp the key concepts, connect them among themselves and have a "map of the territory" as Mr. Pyle says.

The second part shows many techniques for dealing with business situations and how to translate them into a data mining problem. Many of these topics were new for me and I was able to learn and apply a lot of these powerful methodology.

Part 3 is mainly about the data mining algorithms, different approach to solve data mining problems and how to improve the results. Although I knew about this subject, many topics are discussed in a very interesting point of view.

Finally, the part 4 provides a full interactive methodology which summarizes the previous parts. I have found this part very helpful in my work as business modeling consultant.

Summarizing, I think that this book is excellent and it would be read by anyone who wants to apply data analysis to the real world.

Using data to solve busines problems
A must have for any data miner that takes his profession seriously. Already a classic. Business modeling and data mining are carefully separated, as they should be. This crucial distinction has greatly enlightened my view on business problems. First discover the framework for the business problem, determine the leverage point, and then build and refine the best possible model.

All steps are described in practical detail, making the book extremely actionable, and tool independent. First, how to determine the appropriate problem to analyze? Then, what are the right data, and how do I get them? Only then does the data mining begin, and a groundbreaking, comprehensive methodology is put forward to come up with the best possible model in every circumstance. The business modeling and data mining methodologies explicate at every possible step in the process- what to do, and how to proceed. In addition, a lot of supporting material provides insight on topics like working with conditional probabilities, regression to the mean, visualizing model performance and errors in problem space, etc.

Mr. Pyle's previous book set the mark with regards to data preparation. This book is much broader in its scope and should actually be read before the previous one. It's pretty hefty, but more than worth the read. In my opinion it should also be mandatory for `data savvy' marketers as well, for instance as textbook in contemporary MBA courses. ... Read more

Product Description
This scarce antiquarian book is a selection from Kessinger Publishing's Legacy Reprint Series. Due to its age, it may contain imperfections such as marks, notations, marginalia and flawed pages. Because we believe this work is culturally important, we have made it available as part of our commitment to protecting, preserving, and promoting the world's literature. 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

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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
The book has no illustrations or index. Purchasers are entitled to a free trial membership in the General Books Club where they can select from more than a million books without charge. Subjects: History / General; ... Read more

Product Description
The growth of the web can be seen as an expanding public digital library collection. Online digital information extends far beyond the web and its publicly available information. Huge amounts of information are private and are of interest to local communities, such as the records of customers of a business. This information is overwhelmingly text and has its record-keeping purpose, but an automated analysis might be desirable to find patterns in the stored records. Analogous to this data mining is text mining, which also finds patterns and trends in information samples but which does so with far less structured--though with greater immediate utility for users--ingredients. This book focuses on the concepts and methods needed to expand horizons beyond structured, numeric data to automated mining of text samples. It introduces the new world of text mining and examines proven methods for various critical text-mining tasks, such as automated document indexing and information retrieval and search. New research areas are explored, such as information extraction and document summarization, that rely on evolving text-mining techniques. ... Read more

Customer Reviews (5)

it is 200 pages thick
The authors (4 guys) tried to cover all IR big words as much as they can, and ended up with the 221 pages book. Let's take one example, inverted index takes 1.5 pages: It says inverted index is a table with the key-pair. The key is all the keywords scanned from the source, and the value is the document and word position (key in that document), period. IMHO, it is apparent facts that inverted index is like this way. But in practical world algorithm, it is much more complicated than a table, for example, how to incremental fill the index, how to sync between multiple backup copy, how to blabla. And even THAT google paper is more useful than it on this area. People may argue it is a comprehensive introduction book, well, then try Gerald's classic book. The whole impression is like I am reading a C++ programming book which spends 10 pages talking K&R's from Bell, how long they had been there, etc ...
I spent about 1 hr scanning the whole book without much left on my brain . Considering the price 69 bucks, I have to give it 0 on performance/price.

Great introduction book of text mining
This is a great book on text mining. It provides every detail you need to know to build a search engine or text analysis. There are several other books available on similar topics, but this one is definitely the best. Among all the chapters in this book, I like chapter 2 the best. It provides a complete list of solutions to convert the unstructured texts into vectors. Many researchers and enginners are familiar with the process, but few pay attention to many aspects as the book did, such as sentence boundary determination and phrase recognition.

In one word, it is a great introduction book for someone new to the area, also a good handbook to check from time to time.

an idiot savant, statistical viewpoint
The authors give an excellent review of how matters stood in 2004, regarding text mining. The approach of the book is to minimise linguistic and semantic analysis. Instead, it looks more at the statistics of words (tokens) in documents. By using various such methods, they offer an automated way to classify documents. When this works, it can be a tremendous saver of manual effort. Think of the book as perhaps advocating an idiot savant vantage, and seeing how far one can usefully take this approach.

The results of the methods can also be used as input to more advanced and specialised methods, that rely on semantic analysis.

The book can also be applied to search engine analysis.

Very Good Intro Book
I wouldn't give it 5 stars, but definitely worth the money. I took an online class at statistics.com that used this as the text. Really a great combination of book and class and wasn't expensive. Highly recommend both to any data miner interested in getting into text mining.

An excellent introduction
I found the book informative and timely. The book describes the algorithms with psuedocode, and this made it possible for me to apply the algorithms to a legacy structure using another language within a few days of finishing the book.

The book's software (available from their website) requires XML formatted documents for input. ... Read more

Product Description

In 2004, the Government Accountability Office provided a report detailing approximately 200 government-based data-mining projects. While there is comfort in knowing that there are many effective systems, that comfort isn’t worth much unless we can determine that these systems are being effectively and responsibly employed.

Written by one of the most respected consultants in the area of data mining and security, Data Mining for Intelligence, Fraud & Criminal Detection: Advanced Analytics & Information Sharing Technologies reviews the tangible results produced by these systems and evaluates their effectiveness. While CSI-type shows may depict information sharing and analysis that are accomplished with the push of a button, this sort of proficiency is more fiction than reality. Going beyond a discussion of the various technologies, the author outlines the issues of information sharing and the effective interpretation of results, which are critical to any integrated homeland security effort.

Organized into three main sections, the book fully examines and outlines the future of this field with an insider’s perspective and a visionary’s insight.

• Section 1 provides a fundamental understanding of the types of data that can be used in current systems. It covers approaches to analyzing data and clearly delineates how to connect the dots among different data elements
• Section 2 provides real-world examples derived from actual operational systems to show how data is used, manipulated, and interpreted in domains involving human smuggling, money laundering, narcotics trafficking, and corporate fraud
• Section 3 provides an overview of the many information-sharing systems, organizations, and task forces as well as data interchange formats. It also discusses optimal information-sharing and analytical architectures

Currently, there is very little published literature that truly defines real-world systems. Although politics and other factors all play into how much one agency is willing to support the sharing of its resources, many now embrace the wisdom of that path. This book will provide those individuals with an understanding of what approaches are currently available and how they can be most effectively employed.

Customer Reviews (1)

Think of It as a 2-1/2 LB Stimulus Package
Ever 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'smotives on more than one front, not to mention his credibility.


... Read more

Product Description
Mining the Web: Discovering Knowledge from Hypertext Data is the first book devoted entirely to techniques for producing knowledge from the vast body of unstructured Web data. Building on an initial survey of infrastructural issues-including Web crawling and indexing-Chakrabarti examines low-level machine learning techniques as they relate specifically to the challenges of Web mining. He then devotes the final part of the book to applications that unite infrastructure and analysis to bring machine learning to bear on systematically acquired and stored data. Here the focus is on results: the strengths and weaknesses of these applications, along with their potential as foundations for further progress. From Chakrabarti's work-painstaking, critical, and forward-looking-readers will gain the theoretical and practical understanding they need to contribute to the Web mining effort.

* A comprehensive, critical exploration of statistics-based attempts to make sense of Web Mining.
* Details the special challenges associated with analyzing unstructured and semi-structured data.
* Looks at how classical Information Retrieval techniques have been modified for use with Web data.
* Focuses on today's dominant learning methods: clustering and classification, hyperlink analysis, and supervised and semi-supervised learning.
* Analyzes current applications for resource discovery and social network analysis.
* An excellent way to introduce students to especially vital applications of data mining and machine learning technology. ... Read more

Customer Reviews (8)

comprehensive web mining book though 326 pages
I still gave it 5 stars though the effective page number is 326. There are mainly 3 sections in the book --- the first section is 79 pages walks you thru the basic structure of a web search engine, the 2nd one talks about the learning process (clustering, classification and so on), yes, I know it is AI related stuffs, but this book does not have too much equation and is quite readable. From page 203 is the 3rd section --- application which includes page ranking and other interesting topics.

Great coverage, but quite a few errors
The book is an absolute must for those working in information retrieval, and in particular web information retrieval and web mining. These areas are quite hot (again) both for the academics as well as for industry. I personally enjoyed the fact that there is no discussion of semantic web research directions (Jena, OWL etc.) but others might not... The material is quite tightly brought together and very comprehensibly written. However, especially in chapters 4 and 5 there are many pages containing mathematical errors (either in the formulas or in the algorithms described.) For this reason, I rate an otherwise excellent textbook with 4 stars.

Readable, approachable, informative
The field of relevance algorithms for the web is still relatively new and the author provides a clear, informative introduction to the still-developing field. Many references to real problems are discussed, and the author avoids needless use of equations or symbolic logic when a simple textual explanation is more appropriate. This is the book that the authors of "Modelling the Internet and the Web" should have written. Avoid that book, it is a confusing disaster.

The best general purpose book on the subject I've seen
Probably not a book you're going to put on your coffee table, but if you've got any interest in this subject matter at all this is a book worth having.You can flip it open to just about any page and find something interesting.Most of the descriptions in this book move from general to specific, so you can jump around from chapter to chapter getting an overview, or dig more deeply when you want more detail.The references at the end of each chapter are also very useful.Whether you want a survey of the field or are trying to implement something specific, this book is a valuable resource.

A wonderful textbook for machine learning over the web
This book is one of the best computer science textbooks i have ever seen. Apart from the wealth of information and discussion on specific WEB crawling and data mining (chapters 2, 3, 7, 8), chapters 4, 5 and 6 constitute a wonderful summary of machine learning in general.

The book's discussion of unsupervised learning (the EM algorithm, advanced algorithms in which the number of clusters is not known in advance), supervised learning (Bayesian networks, entropian methods, SVMs), semisupervised learning, co-training and rule induction is extraordinary in that it is short, intuitive, does not sacrifice mathematical rigor, and accompanied by examples (all taken from information retreival over the web). ... Read more

Product Description

The Best-Known Algorithms Currently Used in the Data Mining Community
Contributions from recognized leaders in the field

Identifying some of the most influential algorithms that are widely used in the data mining community, The Top Ten Algorithms in Data Mining provides a description of each algorithm, discusses its impact, and reviews current and future research. Thoroughly evaluated by independent reviewers, each chapter focuses on a particular algorithm and is written by either the original authors of the algorithm or world-class researchers who have extensively studied the respective algorithm.

The book concentrates on the following important algorithms: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART. Examples illustrate how each algorithm works and highlight its overall performance in a real-world application. The text covers key topics—including classification, clustering, statistical learning, association analysis, and link mining—in data mining research and development as well as in data mining, machine learning, and artificial intelligence courses.

By naming the leading algorithms in this field, this book encourages the use of data mining techniques in a broader realm of real-world applications. It should inspire more data mining researchers to further explore the impact and novel research issues of these algorithms.

Product Description
Artificial Intelligence (AI) has been around almost as long as computers havebeen. It is only relatively recently, however, that some basic AI techniques havebeen brought to bear on common software problems. This is not a book aboutAI theory. It is a book about utilizing some AI technologies to enhance thevalue of both new and existing applications. The four AI areas covered in thisbook are Speech Recognition, Intelligent Agents, Data Mining, and Rule-BasedSystems. Through sample real-world applications, Sara Rea shows how to makethe AI technologies both accessible and usable. Most books on AI are eitherdense, theoretical text books, or else general-interest trade books. This will bethe first book to show working .NET developers how to incorporate AI intotheir daily work. ... Read more

Customer Reviews (9)

Its not much of Intelligence rather using microsoft stuff
I didnt find AI in the book, as it was marketted

its a good try by the author, but no its not AI.

Its more of using microsoft components and tools

Regards

Building Intelligent .NET Applications
Don't buy this book unless you have a server to play with and an intimate knowledge of Microsoft server-based technology.The author depends on you being able to fill in the rather extended blanks in her intriguing yet very sketchy instructions on how to set up her examples.I had to give the book up as wasted money.It was a shame, since it was obvious, to me at least, that the author knew what she was talking about.She just didn't talk nearly enough for an ordinary mortal to "get it".:-(

The worst book I've on net
This book is really a shame. It is a spot to M$. M$ names are in bold, it only talks about how magnificent is M$.
What about the contents ? bleah ! copy & paste !
Do not buy this book. Use that money for a pizza.

Not Very In-Depth, Not a lot of code examples
I went out and purchased this book based on some good reviews here at Amazon. I was really unimpressed with it. It is much less a primer on how to program "AI" types of apps with .NET, and much more a manual of how to use Microsoft applications like their speech services and data mining.

I do .NET for a living, which is to say that I am probably not an expert but am proficient. This book was not really aimed at .NET programming. It was aimed at "look at these cool MS apps" and "here is how to right click to enable data cubes".What I mean to say here is that when a topic came up like speech recognition, way to much attention was paid to how to use the Microsoft Wizards and Configuration tools, and little or no time was spent on the actual API or coding practices.In some cases no example programming code was provided.

This book was really sub-par compared to many of the other programming books I have purchased in general. I really don't want to be mean to the author, as she seems to really care about the subject matter. IMHO this book just is not very good, does not provide very good examples, and does not show anywhere near enough actual .NET code.

Great primer book on Microsoft technologies for Intelligent Apps
Building Intelligent .NET Applications is an excellent primer book into the world of Artificial Intelligence (AI) in the business world, specifically related to Microsoft technologies.

Building Intelligent .NET Applications is an introduction to the world of Artificial Intelligence (AI) for .NET programmers. It is the first book I have seen that shows professional .NET developers how to incorporate AI into their daily programming. In this accessible guide, developers learn how to enhance new and existing .NET applications with intelligent agents, data mining, rule-based systems, and speech processing.

Sara dives quite deep into four different branches of the vast world of AI with a great balance of conceptual theory, code samples and real world scenarios. She leads the reader though the complete process of obtaining the technologies to full implication with complete code. Both Visual Basic.Net and C# can be downloaded online while the book gives all examples in Visual Basic.Net.

Sara explores four of the most popular AI technologies by building real-world sample applications that readers can use as the basis for their own applications.Some of the more interesting portions include; Applications that talk-critical for companies seeking to automate their call centers, Speech-enabled mobile applications, Multimodal speech applications, Data-mining predictions, which uncover trends and patterns in large quantities of data, Rule-based programming for applications that can be more reactive to their environments, Multiple software agents that are able to keep remote users up to date and sample applications for Windows and the Web.

The book starts out with a one chapter overview called "Instruction" which is exactly that. It introduces the reader to Business Artificial Intelligence and lays the groundwork for the rest of the book.Immediately in chapter two the book dives into Microsoft Speech Server which is the first of four main technologies that are covered in this book.Microsoft Speech Server is covered until Chapter 5 when the book dives into Data-Mining predictions.Chapter 7 gets into Rule-based systems and Chapter 8 into building Agents.

Chapter 9 finishes off the book with an excellent overview of Artificial Intelligence.In fact, for an overview of AI and Microsoft's investment into it now and in the near future, the final chapter of the book was my favorite. Sara painted an exciting picture of what is in store, as well as opening my eyes to things that exist already. AI isn't a thing of the distant future; in fact there is an exciting array of mature technologies in use and available today.

Personally I felt that Chapter 9 would have made a better introduction chapter.I didn't feel that Artificial Intelligent or Business AI was covered in much depth in the first chapter of the book.By the time chapter 2 dove in deep into the first branch of the four topics, I still had some unanswered overview questions in my mind.After reading Chapter 9 though, the need I felt for more general information was met.

Now with Microsoft Speech server, applications that can talk and interact intelligently with a user is not only possible, it's relatively easy and affordable, even for the small business.Developers can create powerful, intelligent applications that are specific to their business.You can create fully database-driven talking applications that understand speech, talk back (not like a rebellious 15-year-old) and respond differently to each unique situation.This can be used for a telephone application, someone sitting in front of a dumb terminal with audio capability or for a fully configured computer application.Dream big, the options are endless, the solutions are within reach.

Running reports against data has been common for decades, but consider intelligent agents that will dig, analyze, determine a new direction to dig by itself, and return relevant patterns and trends in the data that were never discovered before.Sara covers this very topic with theory, code examples, scenarios and clear and precise explanations.

Agents that self perpetuate, learn their new environment and respond accordingly are the way of the future.The most obvious and painfully in-your-face examples are malicious worms and spyware applications.Worms lodge themselves in an environment, take advantage of their new home by finding important information like a list of emails addresses, and then they spread automatically, continuing this vicious cycle.Spyware agents also install themselves in an environment and start interacting with it to get information to send back to their creator.Now, consider the endless possibilities where Agents can be used for good, and are in use today.The author covers this very topic.

I wouldn't say this book is a general overview of Business Intelligent Design, but rather a specific look at four major technologies and a few minor technologies.The Microsoft products covered are Microsoft Visual Studio.Net, Microsoft Speech Server and SASDK, Microsoft SQL Server, Online Analytical Processing (OLAP), BizTalk Server, Microsoft Agent, Background Intelligent Transfer Service (BITS) and I'm sure a couple other smaller technologies that I didn't list.In addition to these, Sara briefly covers SQL Server 2005, Analysis Services 2005, and Longhorn with Avalon, Indigo, and WinFS.

One of the characteristics of a good technical book is making the complex subjects sound simple. The author has done a tremendous job of that in this book. The range of topics that she covers at first glance seems complex, but at no point does she leave the reader overwhelmed. At the same time she doesn't over explain or drag on needlessly.

This book is about the IA (Intelligent Applications) part of AI (Artificial Intelligence). It focuses on Microsoft solutions for Speech solutions, Agents, Data Mining and Rule-Based Systems, and does a great job of it.

The following sample chapters from the book are available online at Addison-Wesley's site:

Data-Mining Predictions

Creating .NET Applications That Talk

[...] ... Read more

Product Description

Building and maintaining a strong and effective team

If two heads are better than one, how about a team of heads? An effective team can be more innovative than an individual. But how do you get there? Building and managing a strong, productive team is difficult and the Mining Group Gold gives you the proven tools, techniques and processes that you must use and practice al all levels of your organization to build and maintain a strong collaborative team.

Based on 30 years of work on teams and organizational development this updated classical guide shows you how to set clear goals and desired outcomes and how to plan efficient and effective meetings. It's also been updated to include the latest research and cutting-edge technology.

The Mining Group Gold features:

• Clear, concise direction for getting the most out of a team's potential
• Effective, practical tips for productive team meetings
• Proven ways to foster collaboration and innovation-crucial skills for any company

Based on practical advice rather than fluff or theory, the Mining Group Gold is the essential guide to building and maintaining a strong team. ... Read more

Customer Reviews (4)

Mining Group Gold - Third Addition
What an outstanding update to one of the most effective books I have ever read and used in my 35 years in the business world. I found this book about five years ago. I work in a large corporate environment, and for many years I attended meetings that were not very effective and therefore, without much meaning. It was very seldom that we ever had a meeting that did much more than set a date for the next meeting. Since I started using the Mining Group Gold format, we have accomplished so much more, in much less time than I thought was possible. Not only have I made this format part of two very successful divisions I have been blessed to champion, but it has now been rolled out through-out the organization. For anyone who has struggled having an effective meeting at any company level, I strongly recommend Mining Group Gold. It has been extremely effective in helping align our entire company.

Timeless and always relevant information
I have been in several leadership roles throughout the years, and never have I come across something as simple and effective as Mining Group Gold.So many organizations struggle and even fail because they are made up of a group of people acting as individuals - not as a team.

One of the biggest frustrations I have come across in my career is ineffective meetings.We have meetings to plan meetings, meetings to re-cap meetings, and meetings just for the sake of meeting.It can be very easy to overlook the amount of time and money that is wasted on meetings that either never needed to happen or should have been conducted in an entirely different manner.Kayser lays out six critical questions to ask yourself when planning for a group meeting, and I have found that by going through this exercise I have saved significant time and money, as well as learned how to more effectively communicate with my team.

I feel that by reading this book, I am now a much better leader and have a better relationship with my staff.Everyone on my team knows that their opinion counts, and I am better able to assess the strengths of my team members and assign them tasks appropriately.No matter what stage you are in your career, Mining Group Gold will make you a better teammate, leader, and organization as a whole.

Get the Most from Your Team - Get the Most from Your Meetings
Repetitive, non-productive meetings.Preaching meetings.Time wasting meetings.I know you've been there, just as I'd been there over many years.This book changed all that forever, for me as well as for my organization.

Mr. Kayser lays out an easy-to-read, easy-to-understand and, best of all, easy to implement format for the reader to put into practice and turn her or his meetings into fruitful sessions of information sharing, of discussion whenever appropriate, of meaningful idea sharing and of satisfying accomplishment.Best of all, it works - in any "meeting", no matter the size, and no matter if it's business, if it's communuity, or if it's personal.

Some time ago, I read "Mining Group Gold".Skeptical at first, I was nonetheless intrigued by Mr. Kayser's processes that claim to turn meetings that are so often sessions of "reading the mail" or "preaching" into sessions of valuable insight instead. I, along with another individual, had a meeting with 60 people scheduled within a week after I completed the book.With this other individual, I dicussed a new approach - the MGG approach - to our meeting.It was a whiole new world for us, and we weren't entirely confident, but Mr. Kayser encourages the reader to just try the processes explained in the book.He advises that the 1st time may not be smooth & perfect, but it will be better than he would have otherwise had.So we literally ripped up the "agenda" we had, and started new, using templates and principles from "Mining Group Gold".The impact was powerful.During wrap up, meeting participants over & over exclaimed that they'd never been in such a productive meeting, or they never thought we would accomplish what we stated as our "desred outcome" at the start of the meeting, or that "it was the best meeting ever attended".

Read the book and benefit from Mr. Kayser's wealth of experience.Learn how to decide if you even need a meeting.Learn how to get the most "gold nuggets" out of the meeting participants - the willing as well as the not-so-willing. Learn how to assure "buy-in" to your group's ideas and plans of action.

I've been in business for over 30 years.No book has ever had as positive an impact on my business life as has "Mining Group Gold". Trust and practice the "Mining group Gold" fundamentals.You'll be glad you did!

I'm a Beleiver!
At the suggestion of a co-worker I read Mining Group Gold and honestly, my first impression was the content was a basic rehash of a well-worn process.In fact, I questioned if MGG could deliver on its promises - to increase productivity of meetings and elevate the collaboration of meetings attendees.

After assisting with the development of a meeting, and subsequent attending meetings organized and managed using MGG I have become a believer. Since that time, I have attending many meetings - some following the MGG process and some not using the MGG process.The MGG process delivers everytime!I've also organized webinar type meetings using MGG and found that MGG works well for these meetings too!

The MGG process forces me as a meeting organizer to think through the "flow" and be well prepared for all challenges.As an attendee, the MGG meeting agenda provides a detailed "snapshot" of the who, what, when, where and why of the meeting and ensures I'm attend well prepared to participate.

Obviously, I'm a believer, and if you follow Kayser's teachings I'm positive you'll become one too!
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Product Description
"This is a first-rate volume that indicates once again that serious scholarship and interesting content are not incompatible." - Colorado Magazine

In the 1850s, the first of hundreds of prospectors went to Colorado to make their fortunes. They took tents and shovels, enthusiasm and cameras. Thus, mining and photography developed simultaneously in Colorado. In this history of the state's most important industry, Duane Smith combines text and photographs to tell the story of Colorado mining from the gold rush of 1859 to the energy crunch of the 1970s.Over the years mining has changed drastically. The individualism that characterized the pioneer period has given way to twentieth-century corporatism: mining giants like Horace Tabor, Meyer Guggenheim, and Winfield Scott Stratton have been replaced by conglomerates like the American Smelting and Refining Company and the Colorado Fuel and Iron Company.This book gives the reader glimpses of the drudgery, hope, and disappointment of miners. The miner, at work and at play, the freighter, railroader, merchant, investor, and scores of others all stood before cameras and thus ensured their own bit of immortality as well as a rich historical record. Smith captures in his text and pictures an era past, but one that produced Colorado today. Colorado scholars and buffs will surely enjoy this book. ... Read more

Customer Reviews (2)

Hard Places:easy to read
Richard V. Francaviglia's "Hard Places: Reading the Landscape of America's Historic Mining Districts" is a well-written and concise treatment of a largely ignored facet of American history and economic development.The author, a Professor of History at University of Texas at Arlington, is clearly an expert in the field and passionate about the subject.Good editing and construction are evident in this University of Iowa production (I am reviewing the hardback version).The book is richly illustrated with black and white photos and numerous maps.Some of the maps are ineffective due to poor reproduction.The book is useful for research with its extensive notes and bibliography.It fills an important gap in the literature and if you are interested in the history of mining towns and how they were shaped, this is an excellent place to begin.

Also of interest by the same author is "Believing in Place: A Spiritual Geography of the Great Basin" published by University of Nevada Press.It is a must-read for Nevada-philes.

Great academic work on mining landscapes
If you're interested in the cultural landscapes associated with mining, this book is a must.Great stuff on Bisbee, AZ.Fantastic maps show the development of that mining landscape over time. ... Read more

Product Description

• Data mining describes the often complex and sophisticated tools used in automatic data analysis such as analyzing a customer's previous buying habits
• Emphasizes the selection of appropriate methodologies and data analysis software, as well as parameter tuning
• Describes representative state-of-the-art methods and algorithms originating from different disciplines
• Offers guidance on how and when to use a particular software tool from among the hundreds offered when faced with a data set to mine
• A Wiley-IEEE Press Publication
• To view the solutions manual, visit ftp://ftp.wiley.com/public/sci_tech_med/data_mining/

Customer Reviews (3)

Good introduction to Neural Networks
I am a graduate student doing thesis related to Neural Networks. I never took any class about Neural Networks before. After reading the chapter "Artificial Neural Networks", I found out that it is very readable for students who are new to Neural Networks. It shows clearly how to calculate/adjust weights with many examples, without overwhelming you with too much Math. I highly recommend this book if you are new to Neural Networks subject.

Pattern recognition or machine learning, not data mining
This book can be used as an introduction to pattern recognition or machine learning rather than into data mining. Data mining does appear here and there, but mostly it is the classical pattern recognition and machine learning material (data reduction, clustering, neural networks) with very few illustrations from data mining. An introduction into genetic algorithms and fuzzy sets is also in the book, just in case, I suppose. If you'd like more specific data mining knowledge, look elsewhere.

Survey, not how-to
The subtitle advertises "concepts, models, methods, and algorithms". Concepts and models, yes; methods, a few; algorithms, nearly none that you could actually code.

This book's strength is its breadth. It offers brief tastes of many topics. It discusses early data preparation, including reduction of dimension and handling of outliers and missing values. It emphasizes that different kinds of questions must be addressed in different ways. The rest of the book then covers decision rules of different sorts, clustering, neural networks, genetic algorithms, fuzzy logic, and data visualization. Each chapter includes references and comments on what to expect from each reference - a nice touch. The end of the book names a wide variety of web sites, products, and companies dedicated to data mining.

The big problem, however, is that the book is shallow. With a few exceptions, it just names techniques instead of giving descriptions that a programmer can use. For example, the discussion of missing data barely mentions the idea that imputed (made-up) values must be tailored to the specific analysis technique, so as to minimize their effect on results. There are exceptions, of course. Neural nets get a relatively detailed treatment. The author gives illustrative examples of genetic algorithms, but those were thin and tangential to data mining. The section on data visualization could have been much more lively. There is a huge body of visual technique, some bordering on artistry, that can present high-dimensional data to the human pattern-detection faculty, and samples are readily available. This book's examples were small and drab, though. Also, it completely ignored the research in auditory and tactile data representation, and omitted discussion of graphic design principles required for effective presentation.

What really bothered me were examples of sheer carelessness. A number of figures, including 4.8 and 9.9, contain errors severe enough to interfere with the point being made. Important relationships are simply illegible. Books like this aren't cheap - I would have hoped that the author would show a little more respect for the people paying the money.

This book may have value as a survey resource, but isn't for the reader who wants to implement the algorithms. Its bibliography is informative, but not a major asset. Indices of current products and web sites nearly guarantee early obsolescence. Look this over thoroughly before you commit your time and money to it. ... Read more