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Abstract

LIS professionals use structures for organizing knowledge when they catalog and classify objects in the collection, when they develop databases, when they design customized taxonomies, or when they search online. Structures for Organizing Knowledge: Exploring Taxonomies, Ontologies, and Other Schema explores and explains this basic function by looking at three questions: 1) How do we organize objects so that they make sense and are useful? 2) What role do categories, classifications, taxonomies, and other structures play in the process of organizing? 3) What do information professionals need to know about organizing behaviors in order to design useful structures for organizing knowledge? Taking a broad, yet specialized approach that is a first in the field, this book answers those questions by examining three threads: traditional structures for organizing knowledge; personal structures for organizing knowledge; and socially-constructed structures for organizing knowledge. Through these threads, it offers avenues for expanding thinking on classification and classification schemes, taxonomy and ontology development, and structures. Both a history of the development of taxonomies and an analysis of current research, theories, and applications, this volume explores a wide array of topics, including the new digital, social aspect of taxonomy development. Examples of subjects covered include: Formal and informal structures Applications of knowledge structures Classification schemes Early taxonomists and their contributions Social networking, bookmarking, and cataloging sites Cataloging codes Standards and best practices Tags, tagging, and folksonomies Descriptive cataloging Metadata schema standards Thought exercises, references, and a list of helpful websites augment each section. A final chapter, "Thinking Ahead: Are We at a Crossroads?" uses "envisioning exercises" to help LIS professionals look into the future.

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Abstract

The Architecture of Cyberspace is aimed at students taking information management as a minor in their course as well as those who manage document collections but who are not professional librarians. The first part of this book looks at how users find documents and the problems they have; the second part discusses how to manage the information space using various tools such as classification and controlled vocabularies. It also explores the general issues of publishing, including legal considerations, as well the main issues of creating and managing archives. Supported by exercises and discussion questions at the end of each chapter, the book includes some sample assignments suitable for use with students of this subject. A glossary is also provided to help readers understand the specialised vocabulary and the key concepts in the design and assessment of information spaces.

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Abstract

The main purpose of this book is to sum up the vital and highly topical research issue of knowledge representation on the Web and to discuss novel solutions by combining benefits of folksonomies and Web 2.0 approaches with ontologies and semantic technologies. This book contains an overview of knowledge representation approaches in past, present and future, introduction to ontologies, Web indexing and in first case the novel approaches of developing ontologies. This title combines aspects of knowledge representation for both the Semantic Web (ontologies) and the Web 2.0 (folksonomies). Currently there is no monographic book which provides a combined overview over these topics. focus on the topic of using knowledge representation methods for document indexing purposes. For this purpose, considerations from classical librarian interests in knowledge representation (thesauri, classification schemes etc.) are included, which are not part of most other books which have a stronger background in computer science.

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Abstract

Class-tested and coherent, this textbook teaches information retrieval, including web search, text classification, and text clustering from basic concepts. Ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students. Slides and additional exercises are available for lecturers. - This book provides what Salton and Van Rijsbergen both failed to achieve. Even more important, unlike some other books in IR, the authors appear to care about making the theory as accessible as possible to the reader, on occasion including short primers to certain topics or choosing to explain difficult concepts using simplified approaches. Its coverage [is] excellent, the quality of writing high and I was surprised how much I learned from reading it. I think the online resources are impressive.

Content

Inhalt: Boolean retrieval - The term vocabulary & postings lists - Dictionaries and tolerant retrieval - Index construction - Index compression - Scoring, term weighting & the vector space model - Computing scores in a complete search system - Evaluation in information retrieval - Relevance feedback & query expansion - XML retrieval - Probabilistic information retrieval - Language models for information retrieval - Text classification & Naive Bayes - Vector space classification - Support vector machines & machine learning on documents - Flat clustering - Hierarchical clustering - Matrix decompositions & latent semantic indexing - Web search basics - Web crawling and indexes - Link analysis Vgl. die digitale Fassung unter: http://nlp.stanford.edu/IR-book/pdf/irbookprint.pdf.

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Abstract

Why we organize our personal digital data the way we do and how design of new PIM systems can help us manage our information more efficiently. Each of us has an ever-growing collection of personal digital data: documents, photographs, PowerPoint presentations, videos, music, emails and texts sent and received. To access any of this, we have to find it. The ease (or difficulty) of finding something depends on how we organize our digital stuff. In this book, personal information management (PIM) experts Ofer Bergman and Steve Whittaker explain why we organize our personal digital data the way we do and how the design of new PIM systems can help us manage our collections more efficiently.