Data Mining: Technologies, Techniques, Tools, and Trends

by Bhavani Thuraisingham

Overview

Focusing on a data-centric perspective, this book provides a complete overview of data mining: its uses, methods, current technologies, commercial products, and future challenges.

Three parts divide Data Mining:

Part I describes technologies for data mining - database systems, warehousing, machine learning, visualization, decision support, statistics, parallel processing, and architectural support for data mining

Part II presents tools and techniques - getting the data ready, carrying out the mining, pruning the results, evaluating outcomes, defining specific approaches, examining a specific technique based on logic programming, and citing literature and vendors for up-to-date information

Part III examines emerging trends - mining distributed and heterogeneous data sources; multimedia data, such as text, images, video; mining data on the World Wide Web; metadata aspects of mining; and privacy issues.

This self-contained book also contains two appendices providing exceptional information on technologies, such as data management, and artificial intelligence.

Is there a need for mining? Do you have the right tools? Do you have the people to do the work? Do you have sufficient funds allocated to the project? All these answers must be answered before embarking on a project. Data Mining provides singular guidance on appropriate applications for specific techniques as well as thoroughly assesses valuable product information.

Product Details

ISBN-13:	9780849318153
Publisher:	Taylor & Francis
Publication date:	12/18/1998
Series:	Database Management/Design Series
Edition description:	New Edition
Pages:	288
Product dimensions:	6.12(w) x 9.19(h) x (d)

About the Author

Thuraisingham, Bhavani

Table of Contents

Introduction Database Systems Data Warehousing Some Other Technologies for Data Mining Architectural Support for Data Mining Data Mining from Start to Finish Data Mining Outcomes, Approaches, and Techniques Logic Programming as a Data Mining Technique Data Mining Tools Mining Distributed, Heterogeneous, and Legacy Databases Data Mining on Multimedia Data Data Mining and the World Wide Web Security and Privacy Issues of Data Mining Metadata Aspects of Mining Summary and Directions References Appendices Data Management Artificial Intelligence

Editorial Reviews

Provides an overview of data mining's uses, methods, technologies, commercial products, and future challenges. Part I describes technologies involved, such as warehousing and visualization, and Part II presents specific tools and techniques. Part III examines emerging trends, including mining distributed and heterogeneous data sources, multimedia data, metadata aspects of mining, and privacy issues. Includes appendices on data management and artificial intelligence. Annotation c. by Book News, Inc., Portland, Or.

Booknews

Dowsing for Data

Reading Data Mining by Bhavani Thuraisingham is a poignant experience. Thuraisingham is aware that the technology she expounds has within it the potential to take away human freedom. Successfully raising the issue, she fails to address it satisfactorily in an otherwise masterful and readable summary of her field.

Data Mining is a scholarly work. The author commences from an epistemological standpoint:

"The actual universe has the truth about all of the entitites in the universe. The perceived universe is the people's view of the universe. This view is usually determined by someone or a group of people in authority."

Indeed. If the credit bureau demurs, you'll be rented no apartment.

"For data modeling purposes, it is the perceived view of the universe that is of interest. This is because the views of the users of the database must be correctly reflected."

Clearly the credit bureau's perceived universe is more valid than your's or mine, because they have paid for the data mining.

"For example, an intelligence agency could determine abnormal behavior of its employees using this technology."

There are fair indications that they already track the behavior of citizens using the Internet. Is being spied on by a chron process more scientific than being tested for witchcraft by being tossed bound into a river to see if you float?

Is it Safeway or Visa who knows best what to do with the record of every prescription you ever purchased, or is it the DEA? How many hits have you made, intentionally or inadvertently, on Web sites containing pornography? Sites that mention legalizing marijuana? Which offer abortion information? Addresses of gay support groups? Guns for sale?

These concerns represent what the author calls the "social and political" aspects that one should "note," in closing Chapter 13 on "Security and Privacy." That chapter, by the way, is mostly about maintaining the security and privacy of the data itself, not the security and privacy of the lives it shadows. "We need the technology first before we can enforce various policies and procedures," Thuraisingham concludes laconically.

Who is mining what inferences from what data? Data Mining shrugs and turns to the more entertaining topic of deceiving "the adversary" and making him doubt his data mining tool and its inferences.

Data Mining is a profound overview of an important domain of human knowledge, as well as a profound reminder, as if one more were needed at the close of the twentieth century, that science is by itself amoral and available to the highest bidder.

Data Mining is not an implementation book; we remain in the domain of theory with a bibliography of practical works. If you are looking for the broad contours of the field depicted by a distinguished expert, Bhavani Thuraisingham, 1997 winner of IEEE's Technical Achievement Award, has produced a memorable opus.
— Dr. Dobb's Electronic Review of Computer Books

Jack Woehr