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Author: Matteo Lissandrini
Publisher: Springer Nature
ISBN: 3031018664
Category : Computers
Languages : en
Pages : 146
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Book Description
Data usually comes in a plethora of formats and dimensions, rendering the exploration and information extraction processes challenging. Thus, being able to perform exploratory analyses in the data with the intent of having an immediate glimpse on some of the data properties is becoming crucial. Exploratory analyses should be simple enough to avoid complicate declarative languages (such as SQL) and mechanisms, and at the same time retain the flexibility and expressiveness of such languages. Recently, we have witnessed a rediscovery of the so-called example-based methods, in which the user, or the analyst, circumvents query languages by using examples as input. An example is a representative of the intended results, or in other words, an item from the result set. Example-based methods exploit inherent characteristics of the data to infer the results that the user has in mind, but may not able to (easily) express. They can be useful in cases where a user is looking for information in an unfamiliar dataset, when the task is particularly challenging like finding duplicate items, or simply when they are exploring the data. In this book, we present an excursus over the main methods for exploratory analysis, with a particular focus on example-based methods. We show how that different data types require different techniques, and present algorithms that are specifically designed for relational, textual, and graph data. The book presents also the challenges and the new frontiers of machine learning in online settings which recently attracted the attention of the database community. The lecture concludes with a vision for further research and applications in this area.
Author: Matteo Lissandrini
Publisher: Springer Nature
ISBN: 3031018664
Category : Computers
Languages : en
Pages : 146
Get Book Here
Book Description
Data usually comes in a plethora of formats and dimensions, rendering the exploration and information extraction processes challenging. Thus, being able to perform exploratory analyses in the data with the intent of having an immediate glimpse on some of the data properties is becoming crucial. Exploratory analyses should be simple enough to avoid complicate declarative languages (such as SQL) and mechanisms, and at the same time retain the flexibility and expressiveness of such languages. Recently, we have witnessed a rediscovery of the so-called example-based methods, in which the user, or the analyst, circumvents query languages by using examples as input. An example is a representative of the intended results, or in other words, an item from the result set. Example-based methods exploit inherent characteristics of the data to infer the results that the user has in mind, but may not able to (easily) express. They can be useful in cases where a user is looking for information in an unfamiliar dataset, when the task is particularly challenging like finding duplicate items, or simply when they are exploring the data. In this book, we present an excursus over the main methods for exploratory analysis, with a particular focus on example-based methods. We show how that different data types require different techniques, and present algorithms that are specifically designed for relational, textual, and graph data. The book presents also the challenges and the new frontiers of machine learning in online settings which recently attracted the attention of the database community. The lecture concludes with a vision for further research and applications in this area.
Author: Chong Ho Alex Yu
Publisher: CRC Press
ISBN: 1000777790
Category : Business & Economics
Languages : en
Pages : 290
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Book Description
This book introduces both conceptual and procedural aspects of cutting-edge data science methods, such as dynamic data visualization, artificial neural networks, ensemble methods, and text mining. There are at least two unique elements that can set the book apart from its rivals. First, most students in social sciences, engineering, and business took at least one class in introductory statistics before learning data science. However, usually these courses do not discuss the similarities and differences between traditional statistics and modern data science; as a result learners are disoriented by this seemingly drastic paradigm shift. In reaction, some traditionalists reject data science altogether while some beginning data analysts employ data mining tools as a “black box”, without a comprehensive view of the foundational differences between traditional and modern methods (e.g., dichotomous thinking vs. pattern recognition, confirmation vs. exploration, single method vs. triangulation, single sample vs. cross-validation etc.). This book delineates the transition between classical methods and data science (e.g. from p value to Log Worth, from resampling to ensemble methods, from content analysis to text mining etc.). Second, this book aims to widen the learner's horizon by covering a plethora of software tools. When a technician has a hammer, every problem seems to be a nail. By the same token, many textbooks focus on a single software package only, and consequently the learner tends to fit the problem with the tool, but not the other way around. To rectify the situation, a competent analyst should be equipped with a tool set, rather than a single tool. For example, when the analyst works with crucial data in a highly regulated industry, such as pharmaceutical and banking, commercial software modules (e.g., SAS) are indispensable. For a mid-size and small company, open-source packages such as Python would come in handy. If the research goal is to create an executive summary quickly, the logical choice is rapid model comparison. If the analyst would like to explore the data by asking what-if questions, then dynamic graphing in JMP Pro is a better option. This book uses concrete examples to explain the pros and cons of various software applications.
Author: Earl Cox
Publisher: Academic Press
ISBN: 0121942759
Category : Computers
Languages : en
Pages : 554
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Book Description
Foundations and ideas -- Principal model types -- Approaches to model building -- Fundamental concepts of fuzzy logic -- Fundamental concepts of fuzzy systems -- Fuzzy SQL and intelligent queries -- Fuzzy clustering -- Fuzzy rule induction -- Fundamental concepts of genetic algorithms -- Genetic resource scheduling optimization -- Genetic tuning of fuzzy models.
Author: C. J. Date
Publisher: Technics Publications
ISBN: 1634629841
Category : Computers
Languages : en
Pages : 243
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Book Description
Along with its companion volume (Database Dreaming Volume II), this book offers a collection of essays on the general topic of relational databases and relational database technology. Most of those essays, though not all, have been published before, but only in journals and magazines that are now hard to find or in books that are now out of print. Here’s a lightly edited excerpt from the preface (so this is the author speaking): I went back and reviewed all of those early essays, looking for ones that seemed worth reviving (or, rather, revising and reviving) at this time. Of course, some of them definitely weren’t! However, out of a total of around 130 original papers, I did find some 20 or so that seemed to me worth preserving and hadn’t already been incorporated in, or superseded by, more recent books of mine. So I tracked down the original versions of those 20 or so papers and set to work. When I was done, though, I found I had somewhere in excess of 600 pages on my hands—too much, in my view, for just one book, and so I split them across two separate volumes. Highlights of the present volume include a discussion of the difficulties involved in providing a relational interface to a nonrelational system; a tutorial on the quantifiers and what happens to them under three-valued logic; an examination of the effect of user defined types on optimization; some thoughts on normalization and database design tools; and caveats regarding certain important database operators, especially outer join and negation.
Author: C. J. Date
Publisher: Technics Publications
ISBN: 1634629051
Category : Computers
Languages : en
Pages : 208
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Book Description
Some things seem so obvious that they don’t need to be spelled out in detail. Or do they? In computing, at least (and probably in any discipline where accuracy and precision are important), it can be quite dangerous just to assume that some given concept is “obvious,” and indeed universally understood. Serious mistakes can happen that way! The first part of this book discusses features of the database field—equality, assignment, naming—where just such an assumption seems to have been made, and it describes some of the unfortunate mistakes that have occurred as a consequence. It also explains how and why the features in question aren’t quite as obvious as they might seem, and it offers some advice on how to work around the problems caused by assumptions to the contrary. Other parts of the book also deal with database issues where devoting some preliminary effort to spelling out exactly what the issues in question entailed could have led to much better interfaces and much more carefully designed languages. The issues discussed include redundancy and indeterminacy; persistence, encapsulation, and decapsulation; the ACID properties of transactions; and types vs. units of measure. Finally, the book also contains a detailed deconstruction of, and response to, various recent pronouncements from the database literature, all of them having to do with relational technology. Once again, the opinions expressed in those pronouncements might seem “obvious” to some people (to the writers at least, presumably), but the fact remains that they’re misleading at best, and in most cases just flat out wrong.
Author: C. J. Date
Publisher: Apress
ISBN: 1484255402
Category : Computers
Languages : en
Pages : 449
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Book Description
Create database designs that scale, meet business requirements, and inherently work toward keeping your data structured and usable in the face of changing business models and software systems. This book is about database design theory. Design theory is the scientific foundation for database design, just as the relational model is the scientific foundation for database technology in general. Databases lie at the heart of so much of what we do in the computing world that negative impacts of poor design can be extraordinarily widespread. This second edition includes greatly expanded coverage of exotic and little understood normal forms such as: essential tuple normal form (ETNF), redundancy free normal form (RFNF), superkey normal form (SKNF), sixth normal form (6NF), and domain key normal form (DKNF). Also included are new appendixes, including one that provides an in-depth look into the crucial notion of data consistency. Sequencing of topics has been improved, and many explanations and examples have been rewritten and clarified based upon the author’s teaching of the content in instructor-led courses. This book aims to be different from other books on design by bridging the gap between the theory of design and the practice of design. The book explains theory in a way that practitioners should be able to understand, and it explains why that theory is of considerable practical importance. Reading this book provides you with an important theoretical grounding on which to do the practical work of database design. Reading the book also helps you in going to and understanding the more academic texts as you build your base of knowledge and expertise. Anyone with a professional interest in database design can benefit from using this book as a stepping-stone toward a more rigorous design approach and more lasting database models. What You Will LearnUnderstand what design theory is and is notBe aware of the two different goals of normalizationKnow which normal forms are truly significant Apply design theory in practice Be familiar with techniques for dealing with redundancy Understand what consistency is and why it is crucially important Who This Book Is For Those having a professional interest in database design, including data and database administrators; educators and students specializing in database matters; information modelers and database designers; DBMS designers, implementers, and other database vendor personnel; and database consultants. The book is product independent.
Author: Michael Gertz
Publisher: Springer Science & Business Media
ISBN: 3642138179
Category : Computers
Languages : en
Pages : 673
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Book Description
This book constitutes the proceedings of the 22nd International Conference on Scientific and Statistical Database Management, SSDBM 2010, held in Heidelberg, Germany in June/July 2010. The 30 long and 11 short papers presented were carefully reviewed and selected from 94 submissions. The topics covered are query processing; scientific data management and analysis; data mining; indexes and data representation; scientific workflow and provenance; and data stream processing.
Author: C.J. Date
Publisher: Technics Publications
ISBN: 1634628349
Category : Computers
Languages : en
Pages : 277
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Book Description
Fifty years of relational. It’s hard to believe the relational model has been around now for over half a century! But it has—it was born on August 19th, 1969, when Codd’s first database paper was published. And Chris Date has been involved with it for almost the whole of that time, working closely with Codd for many years and publishing the very first, and definitive, book on the subject in 1975. In this book’s title essay, Chris offers his own unique perspective (two chapters) on those fifty years. No database professional can afford to miss this one of a kind history. But there’s more to this book than just a little personal history. Another unique feature is an extensive and in depth discussion (nine chapters) of a variety of frequently asked questions on relational matters, covering such topics as mathematics and the relational model; relational algebra; predicates; relation valued attributes; keys and normalization; missing information; and the SQL language. Another part of the book offers detailed responses to critics (four chapters). Finally, the book also contains the text of several recent interviews with Chris Date, covering such matters as RM/V2, XML, NoSQL, The Third Manifesto, and how SQL came to dominate the database landscape.
Author: C.J. Date
Publisher: "O'Reilly Media, Inc."
ISBN: 1491951699
Category : Computers
Languages : en
Pages : 540
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Book Description
No matter what DBMS you are using—Oracle, DB2, SQL Server, MySQL, PostgreSQL—misunderstandings can always arise over the precise meanings of terms, misunderstandings that can have a serious effect on the success of your database projects. For example, here are some common database terms: attribute, BCNF, consistency, denormalization, predicate, repeating group, join dependency. Do you know what they all mean? Are you sure? The New Relational Database Dictionary defines all of these terms and many, many more. Carefully reviewed for clarity, accuracy, and completeness, this book is an authoritative and comprehensive resource for database professionals, with over 1700 entries (many with examples) dealing with issues and concepts arising from the relational model of data. DBAs, database designers, DBMS implementers, application developers, and database professors and students can find the information they need on a daily basis, information that isn’t readily available anywhere else.
Author: C. J. Date
Publisher: "O'Reilly Media, Inc."
ISBN: 1449328016
Category : Computers
Languages : en
Pages : 277
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Book Description
Because databases often stay in production for decades, careful design is critical to making the database serve the needs of your users over years, and to avoid subtle errors or performance problems. In this book, C.J. Date, a leading exponent of relational databases, lays out the principles of good database design.
