Handbook of Data Structures and Applications (Chapman & Hall/CRC Computer & Information Science Series) Review

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(More customer reviews)This is a very useful book to have. It looks to me that the book is a compilation of various research papers by different authors. Provides a unique view to Data structures and their applications.

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Although there are many advanced and specialized texts and handbooks on algorithms, until now there was no book that focused exclusively on the wide variety of data structures that have been reported in the literature. The Handbook of Data Structures and Applications responds to the needs of students, professionals, and researchers who need a mainstream reference on data structures by providing a comprehensive survey of data structures of various types.Divided into seven parts, the text begins with a review of introductory material, followed by a discussion of well-known classes of data structures, Priority Queues, Dictionary Structures, and Multidimensional structures. The editors next analyze miscellaneous data structures, which are well-known structures that elude easy classification. The book then addresses mechanisms and tools that were developed to facilitate the use of data structures in real programs. It concludes with an examination of the applications of data structures. The Handbook is invaluable in suggesting new ideas for research in data structures, and for revealing application contexts in which they can be deployed. Practitioners devising algorithms will gain insight into organizing data, allowing them to solve algorithmic problems more efficiently.

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Database Systems Concepts with Oracle CD Review

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(More customer reviews)This book is a requirement for a course that I am taking. The book is riddled with errors. You can randomly open any page from the book- and you will find typos and confusing text. On some pages, the powerpoint slides for the book do not even match with the text of the book. This is the sixth edition of this textbook. I consider it inexcusable that the book has hundreds of typos even after being published for more than ten years. As another reviewer pointed out, the additional material that is needed for the book -like SQL schemas- do not even exist in the book's website- contrary to what the book claims. Anybody who is considering this book should think twice. Please get it from the library - go through the book for a week to see what I mean- and dump the book for any book that should be better than this.

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The Fourth edition of Database System Concepts has been extensively revised from the 3rd edition. The new edition provides improved coverage of concepts, extensive coverage of new tools and techniques, and updated coverage of database system internals. This text is intended for a first course in databases at the junior or senior undergraduate, or first-year graduate level. Database System Concepts, 4th ed. offers a complete background in the basics of database design, languages, and system implementations. Concepts are presented using intuitive descriptions, and important theoretical results are covered, but formal proofs are omitted.The fundamental concepts and algorithms covered in Database System Concepts 4th ed. are based on those used in existing commercial or experimental database systems.The authors present these concepts and algorithms in a general setting that is not tied to one particular database system.

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Fundamentals of Data Structures in C++ Review

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(More customer reviews)This book treats the subject of algorithm analysis and data structure with great formalism. This book, in my view, is a must for any under grad course. This book lays foundation for a career in systems programming. However, if you only have passing interest in computer science, this is not a book for you.
sunil@liberate.com

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Data Structures and the Standard Template Library Review

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(More customer reviews)Paid about $100 dollars for this book only to find more bugs than a rainforest; frustrating since the author teaches at the university level but the code resembles that of a novice programmer.
Do yourself a favor and go with another book. You're literally better off
crumpling your cash money and throwing it in the trash rather than buying this disappointment.

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Learning in Graphical Models (NATO Science Series D: (closed)) Review

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(More customer reviews)The title of the book is somewhat misleading, in that most of the research papers involve advanced issues concerning one particular graphical model, namely the Bayesian network. For this reason I highly recommend, as a prerequisite to this book, Finn Jensen's "Bayesian Networks and Decision Graphs". Jensen's book is adequate in giving a good introduction and overview of the subject, but not sufficient for calling oneself an "expert" upon successfully digesting it.
To its credit, "Learning in Graphical Models" has several well-written and interesting papers, but the tutorial papers just did not seem enough of an introduction for me to feel comfortable using it as a first source of introduction.
What I find most compelling about Bayesian networks is the fact that they seem both highly modular (which facilitates reusability and network interconnectivity) and can be designed in a semi-rational manner (contrast this with neural-network architectures for which few good algorithms exist for determining size and number of layers). For this reason I imagine they will be important players in future engineering projects that require learning and adaptation.

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In the past decade, a number of different research communitieswithin the computational sciences have studied learning in networks,starting from a number of different points of view. There has beensubstantial progress in these different communities and surprisingconvergence has developed between the formalisms. The awareness ofthis convergence and the growing interest of researchers inunderstanding the essential unity of the subject underlies the currentvolume. Two research communities which have used graphical or networkformalisms to particular advantage are the belief networkcommunity and the neural network community. Belief networksarose within computer science and statistics and were developed withan emphasis on prior knowledge and exact probabilistic calculations.Neural networks arose within electrical engineering, physics andneuroscience and have emphasised pattern recognition and systemsmodelling problems. This volume draws together researchers from thesetwo communities and presents both kinds of networks as instances of ageneral unified graphical formalism. The book focuses on probabilisticmethods for learning and inference in graphical models, algorithmanalysis and design, theory and applications. Exact methods, samplingmethods and variational methods are discussed in detail. Audience: A wide cross-section of computationally orientedresearchers, including computer scientists, statisticians, electricalengineers, physicists and neuroscientists.

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Information Retrieval: Algorithms and Heuristics (The Springer International Series in Engineering and Computer Science) Review

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(More customer reviews)If you're working in the IR industry, or want to develop software in this field, this book is a great starting point. A clarification: this will is not a book for researchers -- instead think of it as a book for advanced practitioners or engineers needing to work in this area. Inside you'll see complete worked examples of several fundamental computations rather than detailed proofs.

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Information Retrieval: Algorithms and Heuristics is acomprehensive introduction to the study of information retrievalcovering both effectiveness and run-time performance. The focus of thepresentation is on algorithms and heuristics used to find documentsrelevant to the user request and to find them fast. Through multipleexamples, the most commonly used algorithms and heuristics needed aretackled. To facilitate understanding and applications, introductionsto and discussions of computational linguistics, natural languageprocessing, probability theory and library and computer science areprovided. While this text focuses on algorithms and not on commercialproduct per se, the basic strategies used by many commercial productsare described. Techniques that can be used to find information on theWeb, as well as in other large information collections, are included.This volume is an invaluable resource for researchers, practitioners,and students working in information retrieval and databases. Forinstructors, a set of Powerpoint slides, including speaker notes, areavailable online from the authors.

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Computer Vision: Algorithms and Applications (Texts in Computer Science) Review

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(More customer reviews)I have been reading the drafts of this book posted on Richard Szeliski's website, [...] , for about an year now. This book is written to cover almost all state-of-the-art research areas in computer vision and provides a solid introduction and reference. Unlike other books on vision, this book is about applications. The chapters are arranged keeping in mind the different key research areas which should be learned by a computer vision student. Apart from providing an overview, every chapter has abundant key references which direct the student for in-depth understanding of a particular area. This book is a welcome addition as literary resource for the computer vision community. Even though Szeliski has kept the digital version freely accessible in his site, this book as a hardbound version with color figures is definitely indispensable for every computer vision student and researcher. After Horn's landmark book, this book is here to stay as the premier computer vision book for years to come. I have started recommending this book for all the undergraduate and graduate students in my lab and I am planning to order a hardbound version for my personal bookshelf.
I strongly recommend this book for every computer vision enthusiast and I definitely feel that this book has the best content to interest people working in different areas of computer vision either in industry or academia. This book is surely the best book to learn computer vision at this point of time.

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Data Structures and the Java Collections Framework Review

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(More customer reviews)Almost three years ago I read a data structures book which used Java for implementation of the topics covered. Perhaps I did not have a solid grasp of the Java language back then, but the book was one of the worst I have come across - I don't even remember the name. "Data Structures and the Java Collections Framework" on the other hand is one of the most up-to-date books available and certainly one that I will remember for quite some time.
Not only does it cover the theory behind many of the fundamental data structures such as arrays, stacks, queues, trees, graphs, maps, etc. but it also illustrates common algorithms required by those data structures. For a book covering this kind of material that would have been enough, but this book excels in showing implementations with the latest version of Java.
Furthermore, this book's purpose is not to teach Object Oriented programming with Java, or the latest features of version 1.5 (Generics, foreach loop, boxing, vararg). The author assumes those were taught in an introductory Java course. Thus, the book does accomplish its goal to teach data structures using Java, and taking advantage of OO design and the latest features of the language. And for those who need a quick refresher two review chapters are included that quickly cover the most commonly used features of Java, as well as javadoc and packages.
As many other technical books, this one contains its share of typos and errors - nothing major though. Later in the book, only parts of the entire implementation of certain data structures are presented, but yet there is no mention that the book's website contains that and more. Also, an introduction to JUnit could have made this book better.
The part that readers will find most useful about Mr. Collins' book is the future applicability of the Java Collections Framework. There are many poorly written books that deal with data structures and books about the Collections Framework. And yet this book does an outstanding job with the two subjects. A great book to learn data structures from - Highly recommended.


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Data Structures & Algorithms in Java with CDROM (Mitchell Waite Signature) Review

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(More customer reviews)I am surprised that most instructors haven't banned this book! It is absolutely one of the best data structures references on the market and with answers provided with the enclosed CD, one perfect "cheat book." Virtually all the standard data structures for an introductory DS&A course are included here with a good explanation behind the rationale used in the implementation of the code. Lafore is a good writer and explains things well, unlike certain authors. The book isn't heavy on the mathematics, which is good for programmers who don't want to get involved with theory. The applets which implement the data structures are particularly nice.
As mentioned in a previous review, trees are not covered well in this book, but most introductory books don't cover them well either. I don't expect to see an analysis of AVL or red-black trees in an introductory book (Cormen's text, which is the standard for grad school, doesn't explain trees well either). In fact, only Schaffer's book does a creditable job of explaining AVL trees but the implementation of the code isn't the greatest. But for linked lists, stacks,queues, and the like, there are few books that are the equal of this one. Buy the book and you'll pass your DS&A class with flying colors!

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Not filled with with obtuse mathematics and difficult proofs, MWSS:Data Structures and Algorithms in Java removes the mystique from DS&A. It does this in two ways. First, the text is written in a straightforward style, making it accessible to anyone. Second, unique new Java demonstration programs, called "Workshop Applets," are provided with the book. These Workshop Applets provide interactive "moving pictures" which the user can control and modify by pressing buttons. The books text describes specific operations the user can carry out with these Workshop Applets, and the applets then reveal the inner workings of an algorithm or data structure.

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Data Mining Techniques in CRM: Inside Customer Segmentation Review

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(More customer reviews)I recently finished reading Data Mining Techniques in CRM: Inside Customer Segmentation. It is a very didactic book written by Tsiptsis and Chorianopoulos. The authors did a very good job in vulgarizing data mining concepts for the reader. That means nearly no formula. But don't misunderstand me, this is not a book only for beginner. Some deep concepts of data mining are presented. The only particularity is that everything is explained with words and pictures. I really appreciated the approach taken by the authors.
The first part of the book explains data mining concepts. Techniques such as clustering, PCA (Principal Component Analysis) and decision trees are introduced. Since clustering is the most used technique in CRM (Customer Relationship Management), it has a particular focus from the authors. Specific topics such as evaluating the clustering results or profiling are discussed. A very interesting chapter is the one showing examples of data marts in CRM applications (retailers, telco and retail banking).
The second part of the book focuses on CRM applications such as segmentation, cross/up-selling, churn, etc. Full chapters are devoted to customer segmentation in banking, retail and telco. These chapters really give detailed information for such projects (data to consider, aggregations, important factors, result interpretation, etc.). It is clear that the authors have a strong experience in CRM.
To conclude, this is an excellent book for any data miner or anybody involved in CRM. The text is clear and pictures are well done (and funny which is rare enough to be mentioned). From basic to advanced topics, the book is a very pleasant journey inside data mining with a clear focus on customer segmentation. Really advised if you're not a fan of formulas.

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Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing Review

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(More customer reviews)The book starts with a prologue of an under-determined linear system and how sparsity constraints help to solve it with the use of a Langrangian. Next the authors introduce the key idea of how certain norms promote sparsity. There are some good diagrams that really help the geometric intuition (though not as good as the ones by Donoho et al. in connection with Lasso). I really love the way they motivate and frame the entire field but still appeal to concept that most people who have studied linear algebra can relate to.
The first 6 chapters are a master piece in pedagogy. Except for the not so-standard usage of Spark as the measurement of coherence among elements of a dictionary. Mutual coherence is common and easier to grasp since it directly address the size of inner products. This leads to a rather jarring switch when RIP is introduced.
I am still puzzled why the authors do not appeal to frame theory. That leads to strange looking reference to self-dual frames and tight frames when the book never talked about frames.
I also wonder why the authors did not cite Boyd's great book. The treatment of log-barrier was sort of just another penalty function. The term log-barrier was never used in the book.
Overall I cannot put the book down and was especially grateful to the authors for introducing iterative shrinkage as a central theme to link many modern numerical algorithms to solve the basic sparse optimization problem.

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This textbook introduces sparse and redundant representations with a focus on applications in signal and image processing. The theoretical and numerical foundations are tackled before the applications are discussed. Mathematical modeling for signal sources is discussed along with how to use the proper model for tasks such as denoising, restoration, separation, interpolation and extrapolation, compression, sampling, analysis and synthesis, detection, recognition, and more. The presentation is elegant and engaging.Sparse and Redundant Representations is intended for graduate students in applied mathematics and electrical engineering, as well as applied mathematicians, engineers, and researchers who are active in the fields of signal and image processing.

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Triangulations and Applications (Mathematics and Visualization) Review

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(More customer reviews)This is an outstanding book. It is clearly written and goes into great detail. There is source code available that is very well designed and clearly commented. (search for Triangulation Template Library) There are ample illustrations to help you visualize the algorithms.
It is a short book but very complete. It has an academic flavor with definitions, theorems, lemmas and extensive references. There are exercises at the end of the chapters so it was designed to be useful as a textbook for a college computer science course.
I bought it to learn the algorithms and techniques on my own, with an eye toward applying them in geometric modeling for computer games. I found it easy to follow and skipped many of the proofs on the first reading. There are several code snippets throughout the text, some are give in pseudo-code and other are C++. They use OpenGL and GLUT to demonstrate the use of the library. The triangulation library is C++ and not directly tied to OpenGL and should be applicable to Direct3D or other graphics APIs.

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This book will serve as a valuable source of information about triangulations for the graduate student and researcher. With emphasis on computational issues, it presents the basic theory necessary to construct and manipulate triangulations. In particular, the book gives a tour through the theory behind the Delaunay triangulation, including algorithms and software issues. It also discusses various data structures used for the representation of triangulations.

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Process Mining: Discovery, Conformance and Enhancement of Business Processes Review

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(More customer reviews)This book is a must-read for everyone who is interested in Process Mining. It covers the fundamentals and basics of this emerging discipline, and it gives a comprehensive overview of the state of the art in the field.
The book is written by Wil van der Aalst, who has started Process Mining research at the Technical University in Eindhoven about twelve years ago, and who has since been in the center of the developments around this new technology.
Be aware that this book is not a practical handbook that explains how to do Process Mining on a step-by-step basis. Instead, it provides a comprehensive overview about the field of Process Mining as a whole. Although the book does not shy away from technical details, it is easy to read. It provides a very good introduction but also highlights the challenges and complexity of Process Mining when dealing with real-life processes. If you prefer to skip the formal definitions you can still get a good overview because there are many concrete examples.

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The first to cover this missing link between data mining and process modeling, this book provides real-world techniques for monitoring and analyzing processes in real time. It is a powerful new tool destined to play a key role in business process management.

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Handbook of Statistical Analysis and Data Mining Applications Review

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(More customer reviews)The "Handbook of Statistical Analysis & Data Mining Applications" is the finest book I have seen on the subject. It is not only a beautifully crafted book, with numerous color graphs, chart, tables, and screen shots, but the statistical discussion is both clear and comprehensive.
The text does not use only one statistical data mining application to display examples, but provides a rather thorough training in the use of both SAS-Enterprise Miner and STATISTICA Data Miner. A section on SPSS Clementine is also provided, giving comparisons between the various packages. Also employed are STATISTICA's C&RT, CHAID, MARSpline, and other data mining and graphical analytic tools.
The text does not burden the typical data mining researcher with the internals of how the various tools work. It is therefore not steeped in equations. Some are to be found, of course, but the emphasis is on understanding the concepts involved and on how to apply these concepts to real data - which is provided to the reader in terms of data tutorials. Specialized datasets have been prepared by both authors and outside experts in various areas of inquiry ranging from entertainment, financial, engineering, clinical psychology, dentistry, demographics, medical informatics, meteorology, astronomy, and more. Each tutorial is associated with data stored on either the associated CD that comes with the book, or which can be downloaded from a companion web site. Worked out examples of how to use data mining techniques on such data is provided to help the reader gain a solid feel for the data mining enterprise. The final third of the book is devoted to a partial selection of the available tutorials. The two earlier chapters demonstrate how to use data mining software for the analysis of data.
I highly recommend this work to anyone having an interest in data mining. I might also add that the Amazon price of $72.37 is truly excellent for an 864 page academic text, having full color tables and screen shots on some one-third of the pages, plus a CD. A bargain indeed.


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Classic Data Structures in C++ Review

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(More customer reviews)Keep this book on your shelf for a long time, you'll look back to it often. The exmaples use STL (standard templete library) so you don't have to worry about the code being useless when it comes to your data struct. Lastly, don't be intimidated by this book; accessible to both the beginner and expert.

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Algorithms and Data Structures in C++ (Computer Science & Engineering) Review

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(More customer reviews)The formulas of (1.3), (1.4), (1.5),(1.6) are all wrong!
Can't believe it, four formulas in first page are all have errors. Maybe the author fell so sleepy when he's writing this book!

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Algorithms and Data Structures in C++ introduces modern issues in the theory of algorithms, emphasizing complexity, graphs, parallel processing, and visualization. To accomplish this, the book uses an appropriate subset of frequently utilized and representative algorithms and applications in order to demonstrate the unique and modern aspects of the C++ programming language. What makes this book so valuable is that many complete C++ programs have been compiled and executed on multiple platforms. Each program presented is a stand-alone functional program. A number of applications that exercise significant features of C++, including templates and polymorphisms, is included. The book is a perfect text for computer science and engineering students in traditional algorithms or data structures courses. It will also benefit professionals in all fields of computer science and engineering.

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Principles of Database & Knowledge-Base Systems, Vol. 1: Classical Database Systems Review

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(More customer reviews)This book goes into the details of database conception and use. It's not completely up to date but tells you everything on relational databases. from theory to the actual used algorithms.

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Classical database technology is oriented toward a well-understood class of applications. Recently the field has attempted to solve the problems associated with new kinds of applications: computer-aided design, software engineering, and others that combine the need to deal with large amounts of data efficiently and the need to support queries in languages that are more expressive than those found in classical database systems. This book attempts to integrate the study of both the new and the classical forms of database systems.

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