Bibliografisk kontrol og emneordskontrol

The scope of this volume will encompass a collection of research papers related to indexing and retrieval of online non-text information. In recent years, the Internet has seen an exponential increase in the number of documents placed online that are not in textual format. These documents appear in a variety of contexts, such as user-generated content sharing websites, social networking websites etc. and formats, includingphotographs, videos, recorded music, data visualizations etc. The prevalence of these contexts and data formats presents a particularly challenging task to information indexing and retrieval research due to many difficulties, such as assigning suitable semantic metadata, processing and extracting non-textual content automatically, and designing retrieval systems that "speak in the native language" of non-text documents.

For book publishers large and small: the #1 guide to creating and distributing metadata for maximum sales. The Metadata Handbook shows how metadata works, enhancing findability, discoverability, and, of course, book sales. It introduces industry standards (think ONIX!) and best practices, and outlines the essential components for successful metadata creation and distribution. This handbook is a must for every publisher, both for print books and for ebooks. The second edition, published in 2015, is fully updated and expanded to include the most recent information on metadata standards, practices, and use in the publishing industry. Topics covered include: - Essential metadata elements - Metadata best practices and certification programs - A focus on ONIX, but a broad view of how metadata works for book publishers - Also covers ISBN, ISNI, ISTC, LCCN, MARC and DOI - Metadata and the future of publishing - Includes a comprehensive glossary of industry & technical terms Reviews "It is a key handbook for all book publishers to use within their respective businesses and to train all of their team members, and should be placed on every desk to answer everyday questions."> "Coauthor Thad McIlroy sums it up best: '... I won't guarantee that metadata will sell your book, but I guarantee that your book won't sell without metadata'." - Kimberly Lew, Publishing Trends

Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod­ els. Computer systems can easily handle mathematical models even when they are complicated and nonlinear (e.g., neural networks). On the other hand, it is not always easy for human users to intuitively understand mathe­ matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com­ puter systems are designed to handle symbolic and numerical information. A large part of our daily communication is based on words. We learn from various media such as books, newspapers, magazines, TV, and the Inter­ net through words. We also communicate with others through words. While words play a central role in human information processing, linguistic models are not often used in the fields of classification and modeling. If there is no goal other than the maximization of accuracy in classification and model­ ing, mathematical models may always be preferred to linguistic models. On the other hand, linguistic models may be chosen if emphasis is placed on interpretability.

Die TNM-Klassifikation ist das international anerkannte und verwendete System zur Bestimmung der klinisch und histopathologisch anatomischen Ausbreitung einer Tumorerkrankung. Dieses System ist aus der engen Zusammenarbeit aller nationalen und internationalen Komitees entstanden und bildet die Grundvoraussetzung einer sinnvollen Befundbeschreibung und somit die Basis einer Therapieform und ihrer Prognose. Nur so ist eine einheitliche Sprache aller Onkologen beim Vergleich ihrer klinischen Befunde und bei der Bewertung ihrer Behandlungsresultate zu erreichen. Die 6. Auflage enthält die ab 2003 gültigen, für einige Tumoren überarbeiteten, neuen Richtlinien der Tumorklassifikation.