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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

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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Content

Bergman and Whittaker report that many of us use hierarchical folders for our personal digital organizing. Critics of this method point out that information is hidden from sight in folders that are often within other folders so that we have to remember the exact location of information to access it. Because of this, information scientists suggest other methods: search, more flexible than navigating folders; tags, which allow multiple categorizations; and group information management. Yet Bergman and Whittaker have found in their pioneering PIM research that these other methods that work best for public information management don't work as well for personal information management. Bergman and Whittaker describe personal information collection as curation: we preserve and organize this data to ensure our future access to it. Unlike other information management fields, in PIM the same user organizes and retrieves the information. After explaining the cognitive and psychological reasons that so many prefer folders, Bergman and Whittaker propose the user-subjective approach to PIM, which does not replace folder hierarchies but exploits these unique characteristics of PIM.