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The Indexing Companion, first published in 2007, gives an overview of indexing for professional indexers, editors, authors, librarians and others who may be called upon to write, contribute to, edit or commission an index. It covers basic principles as well as examining controversial areas. It is based on publishing standards, textbooks, and the consensus of the indexing community, gained from participation in various mailing lists. It discusses a wide range of document formats and subjects that require indexing, as well as dipping into new topics on the edge of indexing such as folksonomies and the semantic web. Some people consider indexing to be a dry topic - at the end of this book people should be thinking of indexing as a challenging and rewarding profession.
Indexes are created to help people find information. Indexers work hard to find the best words to describe the topics covered by their books and collections. This book is an aid to decision making in indexing. It aims to look at decisions that indexers have to make everyday. Many book indexers are created by professional indexers, but others are made by authors and editors. Indexing is part of their job for librarians, museum curators, technical writers and subject specialists. The book provides something of value for all indexers.
Covers the basic principles of indexing, examines controversial areas and speculates on future directions.
An accessible and wide-ranging study of the history of the book within local, national and global contexts.
Here is an accessible, algorithmically oriented guide to some of the most interesting techniques of complexity theory. The book shows that simple algorithms are at the heart of complexity theory. The book is organized by technique rather than by topic. Each chapter focuses on one technique: what it is, and what results and applications it yields.
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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.
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