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Building Intelligent .NET Applications: Agents, Data Mining, Rule-Based Systems, and Speech Processing

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Building Intelligent .NET Applications: Agents, Data Mining, Rule-Based Systems, and Speech Processing


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Shows developers how to enhance both new and existing .NET applications with four powerful Artificial Intelligence technologies

° By using some of the basic technologies of AI, .NET Developers can build better, more useful programs

° Explains by building real-world sample applications, both Windows-based and Webbased, that readers can use as the basis for their own applications

° Covers the use of Intelligent Agents, Data Mining, Rule-Based Systems, and Speech Processing


  • Copyright 2005
  • Dimensions: 7" x 9-1/4"
  • Edition: 1st
  • Book
  • ISBN-10: 0-321-24626-8
  • ISBN-13: 978-0-321-24626-4

Artificial intelligence (AI) has been in existence almost as long as computers. However, only recently have AI techniques been widely incorporated by companies to enhance

traditional business applications.

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

The author 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.

Highlights 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

  • Sample applications for Windows and the Web

With Building Intelligent .NET Applications, developers will learn the basic technologies of AI needed to create practical, time-saving enterprise applications.

© Copyright Pearson Education. All rights reserved.


Source Code

Untitled Document Download the code samples from this book.


Author's Site

Untitled Document The author's web site, which includes code for the book can be found at: www.custsolutions.net

Sample Content

Online Sample Chapters

Building Intelligent .NET Applications: Data-Mining Predictions

Creating .NET Applications That Talk

Downloadable Sample Chapter

Download the Sample Chapters related to this title.

Chapter 2

Chapter 5

Table of Contents



About the Author.


1. Introduction.

2. Creating Applications That Talk.

3. Telephony Applications.

4. Multimodal Speech Applications.

5. Data-Mining Predictions.

6. Applying Data-Mining Predictions.

7. An Evolving Database.

8. Building an Agent.

9. The Future of Enhanced Computing.





Artificial Intelligence (AI) has been around almost as long as computers. It was first introduced in the 1950s, and many scientists soon developed unrealistic expectations surrounding it. Throughout the past fifty years there have been as many advances as disappointments. Most people do not realize that AI-based technologies are being utilized every day. This is because once a technology becomes mainstream, it is generally no longer considered to be AI-related.

Take the things we associate with intelligence—speaking, writing, thinking; these are actually some of the easiest forms for AI to reproduce. The real beauty of our intelligence is that, while not easily seen, it exists deep inside every living cell that performs a specific function. No individual cell is smart enough to function alone. Instead, humans are a complicated network of cells that carry the blueprints for all other cells.

AI is not an all-or-nothing situation. It achieves success through an incredible number of baby steps. The fact that we are not yet able to build a being like Data in Star Trek does not mean we cannot create some very usable applications in our professional lives. Baby steps have already been taken in the form of technological advancements, including optical character recognition (OCR), speech recognition, digital encoding of pictures and data, and smaller, faster computers. All of these are helping to pave the way for AI-based applications.

I work for a company that creates software for state and city legislatures. Our group is constantly under the gun to produce new and innovative software. To be competitive with the other vendors, we have to show that our product is better. Most important, we have to deliver the product on time.

Recently, we were up against a tight deadline and the pressure was starting to mount. People were getting testy and irritable, and everyone seemed to be waiting on the next guy to do their part. One of my colleagues jokingly informed the other developers that we would soon be installing the newly released Microsoft telepathy product. This could be used to read the minds of all the other developers and make sure everyone was on the same page.

Now, of course, there is no Microsoft telepathy software. Even with the phenomenal progress that has taken place in neuroscience, we still do not fully understand how the brain works, much less how to read one another's minds. Still, I can envision a day, not too far off, when we will have software that can anticipate what users are thinking and act on those predictions.

This book is not about reading minds. It is about utilizing a few artificial intelligence technologies to enhance the value of existing and new applications.

The four AI-related areas I cover in this book are not meant to represent everything the field of artificial intelligence has to offer. In fact, they are just a sampling of the somewhat unexplored potential for business-related applications. They are

  • Agents

  • Data mining

  • Rule-based systems

  • Speech processing

Who Is This Book For?

I wrote this book for developers who are not satisfied with "business as usual." For developers who are always looking to improve their code and their skill sets. For developers who surf development Web sites and read technical journals, hoping to make the applications they work on better.

This book is for any developer, contract or in-house, who is building enterprise-wide applications. The applications could range from those running standalone within the company to those dispersed geographically as Web applications. The companies could be of any size, large or small, but large organizations will probably find the most benefits.

Readers already familiar with Microsoft products, and especially with Visual Studio .NET, will get the most out of this book. It focuses on using AI-based techniques with Microsoft products. Readers already familiar with Microsoft SQL Server will be the most comfortable, since all of the applications utilize Transact-SQL (T-SQL) inside stored procedures.

What You Should Know

This book is not an introduction to programming with Visual Studio .NET. Many of the applications featured in the book are Web-based. It is assumed that the reader is already familiar with designing Web-based applications using ASP.NET. Readers should be familiar with such concepts as setting up a virtual directory and executing a Web application on their localhost machine. They should also understand the difference between server-side script and client-side script.

The sample applications are not intentionally complex, but they access code embedded in SQL Stored Procedures. These stored procedures contain some of the application logic in the form of T-SQL statements. The reader should have a basic understanding of T-SQL and know how to view stored procedure code using Microsoft's Enterprise Manager or Query Analyzer.

To simplify common operations such as data access and exception handling, the sample applications utilize Microsoft Application Blocks. These blocks contain code that demonstrates best practices for accessing common functionality. No additional installation steps are necessary for the reader to execute the sample code. However, readers interested in learning more about the functionality available in these blocks should visit the Microsoft Patterns and Practices Web site at http://www.microsoft.com/resources/practices/code.mspx.

A Note about Security

The sample applications in this book were designed to demonstrate key techniques presented in each chapter. Although limited forms of security were considered, readers should not assume that the sample applications are production-ready.

Readers interested in using the sample applications as a starting point for building their own solutions should thoroughly evaluate the code for security weaknesses. The Microsoft MSDN Web site (http://msdn.microsoft.com) contains many helpful resources for writing secure code. One resource readers may want to refer to first is a MSDN Webcast titled "Writing Secure Code—Best Practices." The Webcast, which originally played on October 12, 2004, is available through the Microsoft On-Demand Webcasts Web site at http://www.microsoft.com/seminar/events/webcasts/ondemand.mspx.

Why I Wrote This Book

I am the type of developer who is always pushing the envelope—looking for more. I eagerly await the emergence of new products and technologies, and I am always trying to make the next application I write better than the last one. That being said, I also have a limited amount of time every day to get everything done.

I wrote this book to explore and introduce some interesting technologies and products that I think are either unknown or unexplored. They all revolve around AI-based concepts that have been around for several years. This book seeks to introduce concepts that may have been viewed as too hard in the past.

The world is changing fast, and the development world even faster. Professional software developers do not have time to learn the foundation of every AI-related technology. We barely have enough time to wade through the documentation that accompanies a beta product. What we need is someone to give us an intuitive and standard way for accessing these technologies. We know that AI technologies can be useful, but we need a good way to get to them.

Sample Applications

This book introduces some AI-based concepts using Visual Studio .NET. Starting with Chapter 3, the book will present six practical applications that can be designed with Visual Studio.NET. All the code for the sample applications is available in both Visual Basic and C# versions on the book's Web site at http://www.awprofessional.com/title/0321246268 and http://www.cutsolutions.net.

The first two applications deal with the newly released Microsoft Speech Server product. This product allows you to create Web-based applications that communicate with the user through speech. Speech processing is already important to companies that want to automate their call centers. As society becomes more mobile, speech processing will be critical to enabling mobile workers. Readers interested in learning about this natural interface will want to focus on Chapters 2, 3, and 4.

Starting with Chapter 5, the book switches to utilizing Microsoft Analysis Services. Analysis Services can be used to build data-mining models against historical data in a relational database. These models can then be used to make predictions about the data. Data mining involves more than just querying a database or creating a fancy report for business executives. It involves uncovering trends and patterns in large quantities of data. In many cases, the trends and patterns discovered were not even thought to have existed.

Chapter 7 examines the concept of rule-based programming. Rules encapsulate the business logic of a program and are stored in a central repository. Each rule is assigned a priority, and the series of rules that is applied will depend on the program's input. Programs using this technique can be more reactive to their environments.

Software agents are explored in Chapter 8. Just as a sports agent represents the best interests of an athlete, a software agent is meant to represent the best interests of the user. An agent is generally independent, reactive, personalized, and communicative. Agents that are able to learn from their users are the most valuable and are thought to possess intelligent capabilities.

Why Just Microsoft Technologies?

This book deals exclusively with Microsoft technologies. The primary reason for this is that Microsoft technologies focus on the needs of businesses and therefore are in line with revenue-generating goals. Many developers today are already familiar with Microsoft tools because they serve as the building blocks of some key business applications. This instantly lowers the learning curve needed for exploring AI techniques utilizing them.

Microsoft has dedicated substantial funds to a vast research division, Microsoft Research, that reviews many current AI areas. The division has made many advances toward speech recognition and natural language processing, as will be explored in the first and last chapters.

Microsoft is generous in providing developers with knowledge. The numerous Software Development Kits (SDKs) available for free download from its Web sites are a testament to this. These kits significantly lower the learning curve associated with adopting new technologies. Since the primary goal of this book is to lower the learning curve associated with AI, it makes sense to utilize a few SDK's in the process.

This book is the start of what I hope will be a trend toward making AI-related technologies more accessible and easy to use. I hope to see more and more developers finding creative and insightful ways to harness these technologies. Have fun!

© Copyright Pearson Education. All rights reserved.


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