Introduction to the Design and Analysis of Algorithms (2nd Edition)

Introduction to the Design and Analysis of Algorithms (2nd Edition)
Average customer rating:

Fantastic intro book

Great introductory text!

Great Introduction to Algorithmic Design

One of the better introductions

An Interestingly Different Approach

Introduction to the Design and Analysis of Algorithms (2nd Edition)
Anany V. Levitin
Manufacturer: Addison Wesley
ProductGroup: Book
Binding: Paperback

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ASIN: 0321358287

Book Description

Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, Introduction to the Design and Analysis of Algorithms presents the subject in a truly innovative manner. Written in a reader-friendly style, the book encourages broad problem-solving skills while thoroughly covering the material required for introductory algorithms. The author emphasizes conceptual understanding before the introduction of the formal treatment of each technique. Popular puzzles are used to motivate readers' interest and strengthen their skills in algorithmic problem solving. Other enhancement features include chapter summaries, hints to the exercises, and a solution manual. For those interested in learning more about algorithms.

Customer Reviews:

Fantastic intro book.......2006-09-27

Even though this book is only a few years old, it seems like a well-worn classic. That is not to say that it is outdated and irrelevant; it is exactly the opposite! While my knowledge of algorithms textbooks isn't encyclopedic, I can say that this book was way ahead of the curve in it's layout. Before it, most books presented a bunch of algorithms with some loose affiliations such as being search algorithms or dealing with graphs. This book groups algorithms into major themes and makes it much easier to learn the fundamentals of algorithm design. There have been a new set of algorithms textbooks coming out as late (Kleinberg and Tardos, Dasgupta et al, etc) that have the same approach as this book because it works so well. Don't miss out!

Great introductory text!.......2006-03-10

For those of you who've always wanted to throw the Cormen text out the window rejoice you finally can! This book is an excellent introduction to algorithms. Though not as thorough as the Cormen text it's orders of magnitude more readable!

Great Introduction to Algorithmic Design.......2005-05-09

I recently finished using this book for a course. I found it to be very well written and the presentation was excellent. Most books on algorithms are hard to read and overly mathematical. This book emphasizes more the textual explanation of algorithms for practical applications and not as much on theoretical proofs etc. The exercises at the end of the chapters strongly reinforce the contents and insightful hints to every exercise are given at the end of the book. I thoroughly enjoyed using this book and found it challenging. Other books I used for reference such as the MIT classic Introduction to Algorithms was also useful but much more difficult to understand initially.

One of the better introductions.......2005-03-12

This book presents the field of algorithm analysis from a different perspective. This book attempts to provide you with enough foundation to not only pick common sorting, searching, etc., algorithms for a problem, but shows you how to design new algorithms if need be. The book is an introduction, so keep that in mind. But the foundation it paves should last you a lifetime.

An Interestingly Different Approach.......2003-06-04

The definitive books on algorithms are widely
acknowledged to be those by Donald Knuth, "The Art of
Computer Programming". Very detailed, and with
voluminous problem sets, they have been the standard
for decades.

Along comes this book with its claim of a different
and complementary classification of the field. The
traditional way is, from a top-down vantage, that at
the highest level, you descend from the root to the
various main problem types. Beneath each problem node
would be subclassifications based on the techniques
used to attack that problem. (I could say "solve", but
that is certainly not the case for some problems.)
This is the most natural classification, because you
often get a problem put in front of you, and you start
from there. Problem-driven.

But what if a method to attack problem A and a method
to attack problem B were very similar? Is there a way
to combine these method nodes? In the problem-driven
tree, not really. So what the author suggests is a
method-driven tree, where problems are descendents of
a method. You regard solutions or research into
problems as instantiations of a particular method.
Sound familiar? You can draw analogies with physics,
if you map the methods into the laws of physics. We
should not follow this too literally. But seen from
this vantage, the author's idea is very reasonable. In
physics, the solutions to a problem are (ideally,
anyway) derived ultimately from the laws of physics.

We should not draw a contrast between the author's
suggestions and the prevailing approach too sharply.
At the research level, a competent analyst should be
aware of different problem areas from which solutions
could be drawn, or to which a solution might be
adapted. As a practical matter, it comes down to the
difference in emphasis for most, rather than a
different worldview.

Book Description

This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications. The concepts are introduced gradually in accessible and self-contained stages, while the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software make it an ideal starting point for further study.

Customer Reviews:

More for mathematicians than computer scientist.......2006-09-20

This book introduces the concepts of kernel-based methods and focuses specifically on Support Vector Machines (SVM). It is hard to read and a good background in mathematic is clearly needed. The book has a strong emphasis on SVM starting from the very first line of text. Concepts are well explained, although equations are not clear. The notation doesn't facilitate the reading at all. The book covers linear as well as kernel learning. The kernel trick is well described. It is easy to understand ideas behind SVM while reading the corresponding chapter. Finally a small chapter on SVM applications is proposed. Unfortunately, it only contains typical SVM applications (i.e. standard problems).

I think this book is good if you:

* Have a strong mathematical background
* Work in the specific domain of SVM (or kernel-based methods in general)
* Want to write a research paper about SVM and need the correct notations

However, this book is NOT intended for people who:

* Don't like to read theorems, corollaries and remarks
* Are not interested in reading hundreds of proofs

This is my personal opinion as a computer scientist: this book is definitely written for mathematicians.

A little dry........2006-01-09

The book is a little dry at times. Also, I didn't get a very clear idea of how to select kernel functions, which seems pretty important.

Not even close to an intro..........2004-03-21

Oh Puhleeeezzzzz... How is your vector math??? Remember your linear algebra well? Do you have a background in SVM's? Intuitively able to suck out of thin air the meaning of the Gamma co-efficient as applied to svm's?? You've read all the background papers and remember your formal logic???? No?? too bad..your out of luck..

This book is more aptly titled an Introduction to the Formalisms of SVM's. If your a software engineer trying to implement one of these, forget it.. Be nice if they put that quadratic algorthim psuedocode into something more readable than greek symbology..

If you are trying to build one of these engines, then this book is of absolutely no help, unless you have a background in machine learning and have read all the papers on SVM's. If you can decompose the math into code in your head, then you might find it entertaining... What I don't get is how all the rest of these reviewers can give such "glowing praise" for this book and have it be so completely worthless as an introduction... makes me think some of these are shills..

Bottom line is, if your trying to code a svm, this book will not help. If your trying to understand how to implement a svm, this book will not help. If you are trying to understand how an svm works, this book will not help. If you want to know the mathematical basis for SVM's and like that presentation.. this is the book for you..

Excellent book.......2003-11-19

I just happened to read the reviews on the book on Support vector machines by Nello Cristianini and John Shawe-Taylor. Could not resist adding my own comments about the book. Excellent book. I plan to use the book for the course on "Fundamentals of computer aided engineering" that I teach at the Swiss Federal Institute of Technology, Lausanne (EPFL).

This is it !.......2001-08-31

The book is just great. The appendix on algorithms could have more explanations. Also the application section is a short. It would have been more usuful to take one of these applicaitons and describe it in details. But all in all, the book is excellent.

An Introduction to Parallel Computing: Design and Analysis of Algorithms, Second Edition

Average customer rating:

Too many mistakes.
Worst text book ever written..
Better read Journals than this book
Great book, but...
A sloppily written book

An Introduction to Parallel Computing: Design and Analysis of Algorithms, Second Edition
Ananth Grama , George Karypis , Vipin Kumar , and Anshul Gupta
Manufacturer: Addison Wesley
ProductGroup: Book
Binding: Hardcover

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ASIN: 0201648652

Book Description

This book provides a basic, in-depth look at techniques for the design and analysis of parallel algorithms and for programming them on commercially available parallel platforms. Principles of parallel algorithms design and different parallel programming models are both discussed, with extensive coverage of MPI, POSIX threads, and Open MP. This second edition includes two new chapters on the principles of parallel programming and programming paradigms, as well as new information on portability. For programmers wanting to gain proficiency in all aspects of parallel programming.

Customer Reviews:

Too many mistakes........2006-02-20

I agree with the other reviewers who have said that this book is sloppy. There are just far too many mistakes for a 2nd edition book; very discouraging in an Addison-Wesley print.

The content is OK, and fairly thorough, but as another reviewer noted, there's considerable handwaving going on in some of the explanations.

Bottom line: a cleaned-up 3rd edition could be a very good textbook. Too bad I'm stuck with the 2nd edition :(

Worst text book ever written.........2005-12-02

This book is extremely poorly written. The authors glaze over complex equations and magically come up with answers that don't make any sense. For example, to anyone having taken a prior architecture course the author's are completely wrong in the majority of cache performance analysis done early on in the book. Problems associated with that topic force the reader to dumb-down quite a bit to achieve their "expected" answer.

The user is left in most cases to derive the bizarre math that is involved through the authors' hand-waiving.
One of my personal favorites is from a formula derivation given on page 340, the sequence follows from the text as:

n^2=Ktwnp,
n=Ktwp,
n^2=K^2tw^2p^2, <--what, did I miss something here?
W=K^2tw^2p^2,

On top of that there are numerous typos in the sparse visual examples that do exist. Thus it makes it even more confounding to read through.

If you are evaluating the text for a possible parallel computing course. Don't waste your time or money with this text, your students will thank you. If you are student looking to take a class that uses this text...dropping a brick on your foot might be more enjoyable. If you think I'm a disgruntled student trying to seek revenge, I'm not. I did fine in the course, and I just want to make sure that no one else gets blind-sided by the non-sensical garbage that is this text. If there was a negative rating...this would be below 1 star.

Better read Journals than this book.......2005-11-29

I bought the book a few months ago as textbook for my semester class in high performance computing. After reading the first 3 chapters I realized that this book is a waste. The examples are only solved partially, a lot of jargons (they should have put the terminology in separate table, maybe).

I was hoping, by reading the book I'd learn something essential and got the basic philosophy of high-performance computing/parallel processing. Instead, I got more confused than before reading it! (I used to be real-time software programmer, so the field is not totally new to me). The authors tried to put everything in this small 633-pages book.

Even my professor said it is useless to read the book and refer us to other papers [Robertazzi's papers], and yes, these IEEE/ACM papers are much clearly explained and understood! I also found that a website is much better explaining the concept. Another book is also I guess better: "Fundamentals of Parallel Processing" by Harry F. Jordan and Gita Alaghband.

Don't waste your money on this book.

Great book, but..........2004-04-08

Yes, this is definitely a good book. The discussions on some of the topics are in depth. Parallel algorithm designs are considered from several different angles (mostly from theoretical performance's point of view). One definitely has to get some backgrounds in algorithms before one can digest the contents of this book, thus I recommend this book only for juniors, seniors, graduate students. From the theoretical point of view this book is great, but from the "experimental" point of view is not. It lacks examples and exercises on doing the theory in the actual parallel computers. Thus you have to develop your own MPI (or openMP) understanding and apply it to the topics discussed in this book.

A sloppily written book.......2004-01-18

The content should be accessible to any graduate student but the sloppy writing style has made it unnecessarily difficult to read. Out of the many poorly written places, here is an example. In section 6.3.5 on page 248, it wrote, "Recall from section 9.3.1..." But I am only in chapter 6, how can I recall something from chapter 9. I then checked chapter 9 and found out that the forward reference was not a typo.

"Foundations of Multithreaded, Parallel, and Distributed Programming" by Gregory Andrews is a much better written book. Unfortunately, Gregory's book does not cover the same content.

Introduction to Parallel Computing: Design and Analysis of Parallel Algorithms
Average customer rating:

Just great

Essential 4 any prospective parallel computing professional

Good book on parallel computing

Great details and insightful

Introduction to Parallel Computing: Design and Analysis of Parallel Algorithms
Vipin Kumar , Ananth Grama , Anshul Gupta , and George Karpis
Manufacturer: Benjamin-Cummings Pub Co
ProductGroup: Book
Binding: Textbook Binding

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Customer Reviews:

Just great.......2002-04-25

Excellent introduction to the field, specially for the beginner. There is no other book as clear and concise as this one. If you need an introduction to parallel computing / programming, buy the second edition of this book now!

Essential 4 any prospective parallel computing professional.......2000-11-30

I bought this book when I was a 2nd grade CS student. I planned to start my research project in supercomputing field. So I decided to study the aspects of parallel computing starting by its concepts and programming. As a programmer I found that I would need the general view before coding. Kumar's book is great in which it gives you generalized overview of hardware and software architectures. He and his contributors don't take care of what system nor language you're using. Instead, they want you to learn Parallel Programming. Scientific and non-numerical algorithms are overviewed and explained mathematically. They prove everything they state by using mathematics. I don't know any better way. Do you? It's worth every penny.

Good book on parallel computing.......2000-10-26

This book is a very good one for the parallel computing fields. The most interesting parts of the book to me are the parallel alogrithms design & analysis. The ideas are explained clearly and the exercises are nice too. I would like to recommend this book to all my friends who are interested in parallel computing.

Great details and insightful.......1998-10-28

This one is must for someone who has needs an introductory course for parallel computing. It dealt with the fundamental of parallel computing in terms of algorithms decide.

Practical Introduction to Data Structures and Algorithm Analysis (C++ Edition) (2nd Edition)

Average customer rating:

Depressing
The gears on the cover dont even work!
Anonymous
Very unhelpful book
I normally buy books because they contain information...

Practical Introduction to Data Structures and Algorithm Analysis (C++ Edition) (2nd Edition)
Clifford A. Shaffer
Manufacturer: Prentice Hall
ProductGroup: Book
Binding: Hardcover

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ASIN: 0130284467

Book Description

The author, Cliff Shaffer provides a superior learning tool for those who desire more rigorous data structures and an algorithm analysis book utilizing Java. While the author covers most of the standard data structures, he concentrates on teaching the principles required to select or design a data structure that will best solve a problem. The emphasis is on data structures, and algorithm analysis, not teaching Java. Java is utilized strictly as a tool to illustrate data structures concepts and only the minimal, useful subset of Java is included.

Customer Reviews:

Depressing.......2007-07-14

This book gave me no hope for Analysis of Algorithm and Data Structures class, i have yet to find another book to assist me in this area. the book was so-what easy to read, but the explanation of the concepts is really horrible, dont waste ur money

The gears on the cover dont even work!.......2006-03-21

I have Dr Shaffer as my professor and he is just as boring in real life as his book. He has told us that some of the code segements are broken to make his students figure them out. DONT buy this book... It's not worth the money.

Anonymous.......2006-02-15

I would not reccomend this book for learning about data structures. With incomplete code and scampy sections on core area material, it seems to serve more as a workbook than anything else. In addition to this I find it to be poorly worded which has often caused me to overlook important details or have to read a sentence multiple times to understand what the author is saying. What saves this from being a one star product is the fact that if you do know the material, it can help you review structures but even then, the ackward wording still can slow down a quick read.

Very unhelpful book.......2005-11-29

Dr. Shaffer attempts to address the difficult topic of data structures and fails. Consistently he glosses over important points, or does not describe the implementation of data structures (the buffer pool, for example, is especially poor) adequately and leaves the hapless student confused and frustrated. For a computer scientist who already understands the subject this book may contain a few good points. Indeed, I was able to follow the sections where I had previous training, but when I studied material new to me, I was out of luck.

If you are unlucky enough to have a university that uses this text, consider trying to find a better book to get yourself an adequate understanding of this important subject, because Dr. Shaffer's text won't do that for you.

I normally buy books because they contain information..........2004-11-05

...but this was a mandatory book for my university's two-course Data Structures & Algorithms sequence that all computer scientists and computer engineers must take.

Coming in with a good deal of programming experience, I find that this book is not as clear or as complete as it could be. The sample code snippets throughout tend to be awkwardly implmented with obscure variable names and obtuse datatyping, and more often than not represent 'a' way of accomplishing a task rather than 'the best' way. Finding better ways of doing things is normally left for exercises at the end of the chapter; the answers are not included with the book.

Also, many significant details or comments are skimmed over or are ommitted from the text. Many important (and complex) observations are left as exercises - but again, the answers are not included, so there is no way of validating your answers.

Further, this book is targeted at the C++ language. It is obscene to discuss data structures and algorithms without mentioning the free, prepackaged, and optimized code of the C++ Standard Template Library. Indeed, this book and the code it includes would have benefitted from the ingenious architecture and software engineering behind the STL.

I really hope the campus bookstore will buy this one back when I'm done with it.

Design and Analysis of Randomized Algorithms: Introduction to Design Paradigms (Texts in Theoretical Computer Science. An EATCS Series)

Average customer rating:

Design and Analysis of Randomized Algorithms: Introduction to Design Paradigms (Texts in Theoretical Computer Science. An EATCS Series)
J. Hromkovic
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

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Accessories:

DNA Computing: 12th International Meeting on DNA Computing, DNA12, Seoul, Korea, June 5-9, 2006, Revised Selected Papers (Lecture Notes in Computer Science)
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ASIN: 3540239499

Book Description

Randomness is a powerful phenomenon that can be harnessed to solve various problems in all areas of computer science. Randomized algorithms are often more efficient, simpler and, surprisingly, also more reliable than their deterministic counterparts. Computing tasks exist that require billions of years of computer work when solved using the fastest known deterministic algorithms, but they can be solved using randomized algorithms in a few minutes with negligible error probabilities.

Introducing the fascinating world of randomness, this book systematically teaches the main algorithm design paradigms – foiling an adversary, abundance of witnesses, fingerprinting, amplification, and random sampling, etc. – while also providing a deep insight into the nature of success in randomization. Taking sufficient time to present motivations and to develop the reader's intuition, while being rigorous throughout, this text is a very effective and efficient introduction to this exciting field.

Computer Algorithms: Introduction to Design and Analysis (3rd Edition)

Average customer rating:

poorly executed text
Worst book I ever read
Is really this book so Terrible?
This is not the Algorithms book you are looking for. Move along.
Is this the worst comp sci book at Amazon ?

Computer Algorithms: Introduction to Design and Analysis (3rd Edition)
Sara Baase , and Allen Van Gelder
Manufacturer: Addison Wesley
ProductGroup: Book
Binding: Hardcover

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ASIN: 0201612445

Book Description

Drawing upon combined decades of teaching experience, Professors Sara Baase and Allen Van Gelder have extensively revised this best seller on algorithm design and analysis to make it the most current and accessible book available. This edition features an increased emphasis on algorithm design techniques such as divide-and-conquer and greedy algorithms, along with the addition of new topics and exercises. It continues the tradition of solid mathematical analysis and clear writing style that made it so popular in previous editions.

Customer Reviews:

poorly executed text.......2007-07-23

This textbook is a mess. It is not elegant or clear, and their coverage of certain topics is confusing and deviates from standard practice. If your algorithms class is using this text, find some friends to pool together and get a copy for the exercises if they are used, otherwise take the book from MIT by Rivest et al out of the library and read that.

Introduction to Algorithms

Worst book I ever read.......2006-07-01

I would have rated "0 stars " if poosible in the selection.
Since this is the textbook for my course I have to deal with this book. The way things are mentioned in this book I doubt whether the authors have even understood the concepts right. I think that the authors themselves are confused while writing this book.
If this book is for your course, drop the course before it is too late.

Is really this book so Terrible?.......2006-02-21

if so,it's very pity ,because it is the textbook of my Algorithm class this term.

This is not the Algorithms book you are looking for. Move along........2005-10-05

This book is in a word, bad. The explanations of the algorithms are decent in places but in some areas using the pseudo code provided you could not reproduce a working algorithm. What data structure they are using is sometimes difficult to determine. They also use function calls they do not explain. When reading the book they are constantly referring back to things they talked about chapters ago just by giving an "Algorithm" or figure number. But with the Lemma and definitions and Examples having similar numbers you will spend a lot of time looking for it, how hard would a page number be? Over all I am not happy.

On the plus side the math review at the start of the book is decent and the book is not too wordy.

I have 4 books on algorithms and I still have not found one that I really like, a shame. This book attempts to be a modern update to "The Design and Analysis of Computer Algorithms" -AHO | Hopcroft | Ullman. An update of that book is not what students need. They need a rethinking of how to present algorithms. We are still waiting on that book.

Is this the worst comp sci book at Amazon ?.......2005-08-30

An appalling book.
Boring, poorly written, poorly edited.

Try Algorithm design manual by Steven S. Skiena or Thomas H. Cormen's Introduction to Algorithms or Kleinberg and Tardos'
Algorithm Design or the excellent Introduction to the Design and Analysis of Algorithms by Anany V. Levitin instead of this mish-mash.

An Introduction to the Analysis of Algorithms

Average customer rating:

Not a reference guide
A must have.
Clear and concise
Classic textbook in this field
A very readable chapter on generating functions

An Introduction to the Analysis of Algorithms
Robert Sedgewick , and Philippe Flajolet
Manufacturer: Addison-Wesley Professional
ProductGroup: Book
Binding: Paperback

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Customer Reviews:

Not a reference guide.......2002-08-07

This book is REALLY for coursework : someone who is going to sit down and read and work thru this book sequentially, not randomly like a reference book.
Other than that caveat it does what it promises ably but be aware that it is MATHS heavy and REQUIRES the programme work.

A must have........2001-10-22

I read a lot of books about complexity analysis. And this book is a state of art in the field. Easy to read, and well done.It cover the necessary staff that every new commer to the field should know, can be used as a refference,and it make a good teaching material for graduate student.

Clear and concise.......2001-01-17

This is an excellent book on the analysis of algorithms. More specifically, it is a book on the mathematics needed for the analysis of algorithms. Quite a few algorithms are presented and analyzed in great detail, but the emphasis is on the analysis techniques rather than on the algorithms.

This is in contrast with Cormen,Leiserson and Rivest, or Sedgewick's own "Algorithms" series which emphasize the algorithms rather than the analysis.

If you're looking for a catalog of algorithms along with explanations, you want a different book, but if you want to know how to analyze that bizarre code (which Fred in the next cubicle wrote) and prove that it works well (or doesn't) then this is an excellent choice.

The book is aimed at advanced undergrads/graduate students and assumes a certain amount of mathematical sophistication - i.e. calculus, discrete math, probability, etc.

On the spectrum from "Mathematical Techniques" through "Analysis of Algorithms" and ending up with "Catalog of Algorithms", I would start with Graham, Knuth and Patashnik "Concrete Mathematics", travel through this book, on to Knuth "The Art of Computer Programming", then to Cormen, Leiserson and Rivest, and finally end up with either Sedgewick's "Algorithms" or Skeina's "Algorithm Design Manual".

Classic textbook in this field.......2000-04-01

For a long time analytic combinatorics lacks a good and comprehensive textbook. Almost every learner in this field learns this subject via scattered papers and chapters in different books or journels. The apprearence of this book is so welcome by learners and researchers that it offers a excellent introduction of this powerful and relatively new field. Flajolet and Sedgewick are the famous masters of this field, and this book proves that again. The writing style is succinct, with instant exercise(s) after every important concept and result. The pace of this book is very natural and self-contained. The first half of this book deals with the basic tools used for analysis of algorithm, from the recurrence, generating function, to asymptotic approx. Then it discusses 2 most crucial subjects: trees and permutations. The last 2 chapter turns to strings and words. I found it very readble that there is a typical and core example in every chapter. BTW, since I still haven't finished studying this book, but I must say that Chapter 5 (Asymptotic) is among many textbooks the best introduction to this hard topic so far.

A very readable chapter on generating functions.......1999-02-04

I don't know whether the style of this book is good or not but for me the chapter on generating functions was very readable. At the time of reading I already have read several books for the understanding of generating functions; including Graham, Knuth, and Patashnik's "Concrete Mathematics," which is definitely great but difficult to me. I've got a solid understanding of the subject through two books: Polya et al's "Notes on Introductory Combinatorics" and Sedgewick and Flajolet's.

Introduction to Clustering Large and High-Dimensional Data

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Introduction to Clustering Large and High-Dimensional Data
Jacob Kogan
Manufacturer: Cambridge University Press
ProductGroup: Book
Binding: Paperback

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ASIN: 0521617936

Book Description

There is a growing need for a more automated system of partitioning data sets into groups, or clusters. For example, digital libraries and the World Wide Web continue to grow exponentially, the ability to find useful information increasingly depends on the indexing infrastructure or search engine. Clustering techniques can be used to discover natural groups in data sets and to identify abstract structures that might reside there, without having any background knowledge of the characteristics of the data. Clustering has been used in a variety of areas, including computer vision, VLSI design, data mining, bio-informatics (gene expression analysis), and information retrieval, to name just a few. This book focuses on a few of the most important clustering algorithms, providing a detailed account of these major models in an information retrieval context. The beginning chapters introduce the classic algorithms in detail, while the later chapters describe clustering through divergences and show recent research for more advanced audiences.

Applied CFD Techniques: An Introduction Based on Finite Element Methods

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Applied CFD Techniques: An Introduction Based on Finite Element Methods
Rainald Löhner
Manufacturer: Wiley
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Binding: Hardcover

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Computational fluid dynamics (CFD) is concerned with the efficient numerical solution of the partial differential equations that describe fluid dynamics, and CFD techniques are commonly used in many areas of engineering where fluid behavior is a factor. This book covers the range of topics required for a thorough study and understanding of CFD.

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