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Linda Fetter's popular Handbook of Indexing Techniques is now available for the first time from Information Today, Inc. in a significantly updated fifth edition that will be welcomed by new, aspiring, and occasional indexers and anyone who teaches indexing. As in earlier releases, the fifth edition includes clear explanations of indexing techniques along with many helpful examples. In addition to its easy-to-follow "how-to" coverage, you'll find updated information about indexing seminars and training programs, professional organizations, and indexing standards. Chapter 8, "Electronic Documents," has been expanded to include basic coverage of embedded indexing, Cambridge University Press indexing, XML indexing, ebook indexing, web indexing, and taxonomies. And, for the first time, the book's bibliographic references a rich source of suggestions for further reading appear in two separate appendixes, one organized alphabetically and the other by topic.
Fundamentals of Database Indexing and Searching presents well-known database searching and indexing techniques. It focuses on similarity search queries, showing how to use distance functions to measure the notion of dissimilarity. After defining database queries and similarity search queries, the book organizes the most common and representative index structures according to their characteristics. The author first describes low-dimensional index structures, memory-based index structures, and hierarchical disk-based index structures. He then outlines useful distance measures and index structures that use the distance information to efficiently solve similarity search queries. Focusing on the difficult dimensionality phenomenon, he also presents several indexing methods that specifically deal with high-dimensional spaces. In addition, the book covers data reduction techniques, including embedding, various data transforms, and histograms. Through numerous real-world examples, this book explores how to effectively index and search for information in large collections of data. Requiring only a basic computer science background, it is accessible to practitioners and advanced undergraduate students.
Indexing: A Practical Guide for Technical Writers is a nuts-and-bolts guide to indexing. It explains in plain language and by example exactly how to index any type of print or online publication quickly, easily, and effectively. The sequential indexing method presented in the book has been battle-tested in high pressure publishing organizations in a variety of high-tech industries over the space of a decade. Because it is based on real-world success, this indexing method is bulletproof. Users of this guide will succeed as an indexer. Unlike other books on the subject, this book is focused on readers, not the subject itself. The book speaks directly to highly practical and often anti-academic technical writers who demand usability, reusability, and reliability. It is geared to people with ""Keep It Simple, Stupid"" signs on their cubicle walls. Proven end-user documentation techniques are employed to present proven indexing methods to readers who themselves develop end-user documentation for a living. They have zero tolerance for academic white papers on indexing. So, the book delivers the hard facts.
Since 1994, Nancy Mulvany's Indexing Books has been the gold standard for thousands of professional indexers, editors, and authors. This long-awaited second edition, expanded and completely updated, will be equally revered. Like its predecessor, this edition of Indexing Books offers comprehensive, reliable treatment of indexing principles and practices relevant to authors and indexers alike. In addition to practical advice, the book presents a big-picture perspective on the nature and purpose of indexes and their role in published works. New to this edition are discussions of "information overload" and the role of the index, open-system versus closed-system indexing, electronic submission and display of indexes, and trends in software development, among other topics. Mulvany is equally comfortable focusing on the nuts and bolts of indexing—how to determine what is indexable, how to decide the depth of an index, and how to work with publisher instructions—and broadly surveying important sources of indexing guidelines such as The Chicago Manual of Style, Sun Microsystems, Oxford University Press, NISO TR03, and ISO 999. Authors will appreciate Mulvany's in-depth consideration of the costs and benefits of preparing one's own index versus hiring a professional, while professional indexers will value Mulvany's insights into computer-aided indexing. Helpful appendixes include resources for indexers, a worksheet for general index specifications, and a bibliography of sources to consult for further information on a range of topics. Indexing Books is both a practical guide and a manifesto about the vital role of the human-crafted index in the Information Age. As the standard indexing reference, it belongs on the shelves of everyone involved in writing and publishing nonfiction books.
A guide for constructing and using composite indicators for policy makers, academics, the media and other interested parties. In particular, this handbook is concerned with indicators which compare and rank country performance.
For decades, optimization methods such as Fuzzy Logic, Artificial Neural Networks, Firefly, Simulated annealing, and Tabu search, have been capable of handling and tackling a wide range of real-world application problems in society and nature. Analysts have turned to these problem-solving techniques in the event during natural disasters and chaotic systems research. The Handbook of Research on Artificial Intelligence Techniques and Algorithms highlights the cutting edge developments in this promising research area. This premier reference work applies Meta-heuristics Optimization (MO) Techniques to real world problems in a variety of fields including business, logistics, computer science, engineering, and government. This work is particularly relevant to researchers, scientists, decision-makers, managers, and practitioners.
The rapidly increasing volume of information contained in relational databases places a strain on databases, performance, and maintainability: DBAs are under greater pressure than ever to optimize database structure for system performance and administration. Physical Database Design discusses the concept of how physical structures of databases affect performance, including specific examples, guidelines, and best and worst practices for a variety of DBMSs and configurations. Something as simple as improving the table index design has a profound impact on performance. Every form of relational database, such as Online Transaction Processing (OLTP), Enterprise Resource Management (ERP), Data Mining (DM), or Management Resource Planning (MRP), can be improved using the methods provided in the book. The first complete treatment on physical database design, written by the authors of the seminal, Database Modeling and Design: Logical Design, Fourth Edition Includes an introduction to the major concepts of physical database design as well as detailed examples, using methodologies and tools most popular for relational databases today: Oracle, DB2 (IBM), and SQL Server (Microsoft) Focuses on physical database design for exploiting B+tree indexing, clustered indexes, multidimensional clustering (MDC), range partitioning, shared nothing partitioning, shared disk data placement, materialized views, bitmap indexes, automated design tools, and more!
Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.