Designing Data-Intensive Web Applications

Free sample

The most prominent Web applications in use today are data-intensive. Scores of database management systems across the Internet access and maintain large amounts of structured data for e-commerce, on-line trading, banking, digital libraries, and other high-volume sites.

Developing and maintaining these data-intensive applications is an especially complex, multi-disciplinary activity, requiring all the tools and techniques that software engineering can provide. This book represents a breakthrough for Web application developers. Using hundreds of illustrations and an elegant intuitive modeling language, the authors—all internationally-known database researchers—present a methodology that fully exploits the conceptual modeling approach of software engineering, from idea to application. Readers will learn not only how to harness the design technologies of relational databases for use on the Web, but also how to transform their conceptual designs of data-intensive Web applications into effective software components.

* A fully self-contained introduction and practitioner's guide suitable for both technical and non-technical members of staff, as well as students.

* A methodology, development process, and notation (WebML) based on common practice but optimized for the unique challenges of high-volume Web applications.

* Completely platform- and product-independent; even the use of WebML is optional.

* Based on well-known industry standards such as UML and the Entity Relationship Model.

* Enhanced by its own Web site (http://www.webml.org), containing additional examples, papers, teaching materials, developers' resources, and exercises with solutions.
Read more

About the author

Stefano Ceri is Professor of Database Systems at Politecnico di Milano. His research interests are focused on extending database technology to incorporate data distribution, deductive and active rules, and object orientation.

Piero Fraternali is professor of Information Systems at Politecnico di Milano.

Marco Brambilla is actively researching on methods and tools for model-driven software development, with special focus on web applications, search engines, social networks and crowdsourcing platforms. He is professor of software engineering and researcher at Politecnico di Milano and partner of the spinoff WebRatio, which produces MDD tools based on IFML, UML, and BPMN. He is the principal contributor of the Interaction Flow Modeling Language (IFML). He authored several books, including Developing Data-Intensive Web Applications (Morgan Kaufmann, 2002) and Model-driven Software Engineering in Practice (Morgan&Claypool, 2012).

Read more
Loading...

Additional Information

Publisher
Elsevier
Read more
Published on
Jan 4, 2003
Read more
Pages
562
Read more
ISBN
9780080503936
Read more
Read more
Best For
Read more
Language
English
Read more
Genres
Computers / Databases / General
Computers / Internet / General
Read more
Content Protection
This content is DRM protected.
Read more

Reading information

Smartphones and Tablets

Install the Google Play Books app for Android and iPad/iPhone. It syncs automatically with your account and allows you to read online or offline wherever you are.

Laptops and Computers

You can read books purchased on Google Play using your computer's web browser.

eReaders and other devices

To read on e-ink devices like the Sony eReader or Barnes & Noble Nook, you'll need to download a file and transfer it to your device. Please follow the detailed Help center instructions to transfer the files to supported eReaders.
Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining.

Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research.

The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise.

Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projectsOffers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methodsIncludes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization
Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining.

This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining.

Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projectsAddresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fieldsProvides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data
Interaction Flow Modeling Language describes how to apply model-driven techniques to the problem of designing the front end of software applications, i.e., the user interaction. The book introduces the reader to the novel OMG standard Interaction Flow Modeling Language (IFML). Authors Marco Brambilla and Piero Fraternali are authors of the IFML standard and wrote this book to explain the main concepts of the language. They effectively illustrate how IFML can be applied in practice to the specification and implementation of complex web and mobile applications, featuring rich interactive interfaces, both browser based and native, client side components and widgets, and connections to data sources, business logic components and services.

Interaction Flow Modeling Language provides you with unique insight into the benefits of engineering web and mobile applications with an agile model driven approach. Concepts are explained through intuitive examples, drawn from real-world applications. The authors accompany you in the voyage from visual specifications of requirements to design and code production. The book distills more than twenty years of practice and provides a mix of methodological principles and concrete and immediately applicable techniques.

Learn OMG’s new IFML standard from the authors of the standard with this approachable referenceIntroduces IFML concepts step-by-step, with many practical examples and an end-to-end case exampleShows how to integrate IFML with other OMG standards including UML, BPMN, CWM, SoaML and SysMLDiscusses how to map models into code for a variety of web and mobile platforms and includes many useful interface modeling patterns and best practices
This book discusses how model-based approaches can improve the daily practice of software professionals. This is known as Model-Driven Software Engineering (MDSE) or, simply, Model-Driven Engineering (MDE).

MDSE practices have proved to increase efficiency and effectiveness in software development, as demonstrated by various quantitative and qualitative studies. MDSE adoption in the software industry is foreseen to grow exponentially in the near future, e.g., due to the convergence of software development and business analysis.

The aim of this book is to provide you with an agile and flexible tool to introduce you to the MDSE world, thus allowing you to quickly understand its basic principles and techniques and to choose the right set of MDSE instruments for your needs so that you can start to benefit from MDSE right away.

The book is organized into two main parts.

The first part discusses the foundations of MDSE in terms of basic concepts (i.e., models and transformations), driving principles, application scenarios, and current standards, like the well-known MDA initiative proposed by OMG (Object Management Group) as well as the practices on how to integrate MDSE in existing development processes. The second part deals with the technical aspects of MDSE, spanning from the basics on when and how to build a domain-specific modeling language, to the description of Model-to-Text and Model-to-Model transformations, and the tools that support the management of MDSE projects.

The second edition of the book features:

a set of completely new topics, including: full example of the creation of a new modeling language (IFML), discussion of modeling issues and approaches in specific domains, like business process modeling, user interaction modeling, and enterprise architecture complete revision of examples, figures, and text, for improving readability, understandability, and coherence better formulation of definitions, dependencies between concepts and ideas addition of a complete index of book content

In addition to the contents of the book, more resources are provided on the book's website http://www.mdse-book.com, including the examples presented in the book.

©2018 GoogleSite Terms of ServicePrivacyDevelopersArtistsAbout Google
By purchasing this item, you are transacting with Google Payments and agreeing to the Google Payments Terms of Service and Privacy Notice.