Search (23 results, page 1 of 2)

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Content

Inhalt: Introduction Document File Preparation - Manual Indexing - Information Extraction - Vector Space Modeling - Matrix Decompositions - Query Representations - Ranking and Relevance Feedback - Searching by Link Structure - User Interface - Book Format Document File Preparation Document Purification and Analysis - Text Formatting - Validation - Manual Indexing - Automatic Indexing - Item Normalization - Inverted File Structures - Document File - Dictionary List - Inversion List - Other File Structures Vector Space Models Construction - Term-by-Document Matrices - Simple Query Matching - Design Issues - Term Weighting - Sparse Matrix Storage - Low-Rank Approximations Matrix Decompositions QR Factorization - Singular Value Decomposition - Low-Rank Approximations - Query Matching - Software - Semidiscrete Decomposition - Updating Techniques Query Management Query Binding - Types of Queries - Boolean Queries - Natural Language Queries - Thesaurus Queries - Fuzzy Queries - Term Searches - Probabilistic Queries Ranking and Relevance Feedback Performance Evaluation - Precision - Recall - Average Precision - Genetic Algorithms - Relevance Feedback Searching by Link Structure HITS Method - HITS Implementation - HITS Summary - PageRank Method - PageRank Adjustments - PageRank Implementation - PageRank Summary User Interface Considerations General Guidelines - Search Engine Interfaces - Form Fill-in - Display Considerations - Progress Indication - No Penalties for Error - Results - Test and Retest - Final Considerations Further Reading

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Vector spaces

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Vector spaces

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Abstract

Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory. As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. Knowledge extraction or creation from text requires systematic yet reliable processing that can be codified and adapted for changing needs and environments. This book will draw upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. It will address document identification, clustering and categorizing documents, cleaning text, and visualizing semantic models of text.

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Content

Inhalt: Chapter 1. Introduction to Web Search Engines: 1.1 A Short History of Information Retrieval - 1.2 An Overview of Traditional Information Retrieval - 1.3 Web Information Retrieval Chapter 2. Crawling, Indexing, and Query Processing: 2.1 Crawling - 2.2 The Content Index - 2.3 Query Processing Chapter 3. Ranking Webpages by Popularity: 3.1 The Scene in 1998 - 3.2 Two Theses - 3.3 Query-Independence Chapter 4. The Mathematics of Google's PageRank: 4.1 The Original Summation Formula for PageRank - 4.2 Matrix Representation of the Summation Equations - 4.3 Problems with the Iterative Process - 4.4 A Little Markov Chain Theory - 4.5 Early Adjustments to the Basic Model - 4.6 Computation of the PageRank Vector - 4.7 Theorem and Proof for Spectrum of the Google Matrix Chapter 5. Parameters in the PageRank Model: 5.1 The a Factor - 5.2 The Hyperlink Matrix H - 5.3 The Teleportation Matrix E Chapter 6. The Sensitivity of PageRank; 6.1 Sensitivity with respect to alpha - 6.2 Sensitivity with respect to H - 6.3 Sensitivity with respect to vT - 6.4 Other Analyses of Sensitivity - 6.5 Sensitivity Theorems and Proofs Chapter 7. The PageRank Problem as a Linear System: 7.1 Properties of (I - alphaS) - 7.2 Properties of (I - alphaH) - 7.3 Proof of the PageRank Sparse Linear System Chapter 8. Issues in Large-Scale Implementation of PageRank: 8.1 Storage Issues - 8.2 Convergence Criterion - 8.3 Accuracy - 8.4 Dangling Nodes - 8.5 Back Button Modeling
Chapter 9. Accelerating the Computation of PageRank: 9.1 An Adaptive Power Method - 9.2 Extrapolation - 9.3 Aggregation - 9.4 Other Numerical Methods Chapter 10. Updating the PageRank Vector: 10.1 The Two Updating Problems and their History - 10.2 Restarting the Power Method - 10.3 Approximate Updating Using Approximate Aggregation - 10.4 Exact Aggregation - 10.5 Exact vs. Approximate Aggregation - 10.6 Updating with Iterative Aggregation - 10.7 Determining the Partition - 10.8 Conclusions Chapter 11. The HITS Method for Ranking Webpages: 11.1 The HITS Algorithm - 11.2 HITS Implementation - 11.3 HITS Convergence - 11.4 HITS Example - 11.5 Strengths and Weaknesses of HITS - 11.6 HITS's Relationship to Bibliometrics - 11.7 Query-Independent HITS - 11.8 Accelerating HITS - 11.9 HITS Sensitivity Chapter 12. Other Link Methods for Ranking Webpages: 12.1 SALSA - 12.2 Hybrid Ranking Methods - 12.3 Rankings based on Traffic Flow Chapter 13. The Future of Web Information Retrieval: 13.1 Spam - 13.2 Personalization - 13.3 Clustering - 13.4 Intelligent Agents - 13.5 Trends and Time-Sensitive Search - 13.6 Privacy and Censorship - 13.7 Library Classification Schemes - 13.8 Data Fusion Chapter 14. Resources for Web Information Retrieval: 14.1 Resources for Getting Started - 14.2 Resources for Serious Study Chapter 15. The Mathematics Guide: 15.1 Linear Algebra - 15.2 Perron-Frobenius Theory - 15.3 Markov Chains - 15.4 Perron Complementation - 15.5 Stochastic Complementation - 15.6 Censoring - 15.7 Aggregation - 15.8 Disaggregation

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Content

SESSION: A digital libraries for education Middle school children's use of the ARTEMIS digital library (June Abbas, Cathleen Norris, Elliott Soloway) - Partnership reviewing: a cooperative approach for peer review of complex educational resources (John Weatherley, Tamara Sumner, Michael Khoo, Michael Wright, Marcel Hoffmann) - A digital library for geography examination resources (Lian-Heong Chua, Dion Hoe-Lian Goh, Ee-Peng Lim, Zehua Liu, Rebecca Pei-Hui Ang) - Digital library services for authors of learning materials (Flora McMartin, Youki Terada) SESSION: Novel search environments Integration of simultaneous searching and reference linking across bibliographic resources on the web (William H. Mischo, Thomas G. Habing, Timothy W. Cole) - Exploring discussion lists: steps and directions (Paula S. Newman) - Comparison of two approaches to building a vertical search tool: a case study in the nanotechnology domain (Michael Chau, Hsinchun Chen, Jialun Qin, Yilu Zhou, Yi Qin, Wai-Ki Sung, Daniel McDonald) SESSION: Video and multimedia digital libraries A multilingual, multimodal digital video library system (Michael R. Lyu, Edward Yau, Sam Sze) - A digital library data model for music (Natalia Minibayeva, Jon W. Dunn) - Video-cuebik: adapting image search to video shots (Alexander G. Hauptmann, Norman D. Papernick) - Virtual multimedia libraries built from the web (Neil C. Rowe) - Multi-modal information retrieval from broadcast video using OCR and speech recognition (Alexander G. Hauptmann, Rong Jin, Tobun Dorbin Ng) SESSION: OAI application Extending SDARTS: extracting metadata from web databases and interfacing with the open archives initiative (Panagiotis G. Ipeirotis, Tom Barry, Luis Gravano) - Using the open archives initiative protocols with EAD (Christopher J. Prom, Thomas G. Habing) - Preservation and transition of NCSTRL using an OAI-based architecture (H. Anan, X. Liu, K. Maly, M. Nelson, M. Zubair, J. C. French, E. Fox, P. Shivakumar) - Integrating harvesting into digital library content (David A. Smith, Anne Mahoney, Gregory Crane) SESSION: Searching across language, time, and space Harvesting translingual vocabulary mappings for multilingual digital libraries (Ray R. Larson, Fredric Gey, Aitao Chen) - Detecting events with date and place information in unstructured text (David A. Smith) - Using sharable ontology to retrieve historical images (Von-Wun Soo, Chen-Yu Lee, Jaw Jium Yeh, Ching-chih Chen) - Towards an electronic variorum edition of Cervantes' Don Quixote:: visualizations that support preparation (Rajiv Kochumman, Carlos Monroy, Richard Furuta, Arpita Goenka, Eduardo Urbina, Erendira Melgoza)
SESSION: Federating and harvesting metadata DP9: an OAI gateway service for web crawlers (Xiaoming Liu, Kurt Maly, Mohammad Zubair, Michael L. Nelson) - The Greenstone plugin architecture (Ian H. Witten, David Bainbridge, Gordon Paynter, Stefan Boddie) - Building FLOW: federating libraries on the web (Anna Keller Gold, Karen S. Baker, Jean-Yves LeMeur, Kim Baldridge) - JAFER ToolKit project: interfacing Z39.50 and XML (Antony Corfield, Matthew Dovey, Richard Mawby, Colin Tatham) - Schema extraction from XML collections (Boris Chidlovskii) - Mirroring an OAI archive on the I2-DSI channel (Ashwini Pande, Malini Kothapalli, Ryan Richardson, Edward A. Fox) SESSION: Music digital libraries HMM-based musical query retrieval (Jonah Shifrin, Bryan Pardo, Colin Meek, William Birmingham) - A comparison of melodic database retrieval techniques using sung queries (Ning Hu, Roger B. Dannenberg) - Enhancing access to the levy sheet music collection: reconstructing full-text lyrics from syllables (Brian Wingenroth, Mark Patton, Tim DiLauro) - Evaluating automatic melody segmentation aimed at music information retrieval (Massimo Melucci, Nicola Orio) SESSION: Preserving, securing, and assessing digital libraries A methodology and system for preserving digital data (Raymond A. Lorie) - Modeling web data (James C. French) - An evaluation model for a digital library services tool (Jim Dorward, Derek Reinke, Mimi Recker) - Why watermark?: the copyright need for an engineering solution (Michael Seadle, J. R. Deller, Jr., Aparna Gurijala) SESSION: Image and cultural digital libraries Time as essence for photo browsing through personal digital libraries (Adrian Graham, Hector Garcia-Molina, Andreas Paepcke, Terry Winograd) - Toward a distributed terabyte text retrieval system in China-US million book digital library (Bin Liu, Wen Gao, Ling Zhang, Tie-jun Huang, Xiao-ming Zhang, Jun Cheng) - Enhanced perspectives for historical and cultural documentaries using informedia technologies (Howard D. Wactlar, Ching-chih Chen) - Interfaces for palmtop image search (Mark Derthick)

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Abstract

Philosophy and Computing explores each of the following areas of technology: the digital revolution; the computer; the Internet and the Web; CD-ROMs and Mulitmedia; databases, textbases, and hypertexts; Artificial Intelligence; the future of computing. Luciano Floridi shows us how the relationship between philosophy and computing provokes a wide range of philosophical questions: is there a philosophy of information? What can be achieved by a classic computer? How can we define complexity? What are the limits of quantam computers? Is the Internet an intellectual space or a polluted environment? What is the paradox in the Strong Artificial Intlligence program? Philosophy and Computing is essential reading for anyone wishing to fully understand both the development and history of information and communication technology as well as the philosophical issues it ultimately raises. 'The most careful and scholarly book to be written on castles in a generation.'

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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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Date

23. 3.2008 19:10:22

Footnote

Rez. in: JASIST 54(2003) no.9, S.905-906 (C.A. Badurek): "Visual approaches for knowledge discovery in very large databases are a prime research need for information scientists focused an extracting meaningful information from the ever growing stores of data from a variety of domains, including business, the geosciences, and satellite and medical imagery. This work presents a summary of research efforts in the fields of data mining, knowledge discovery, and data visualization with the goal of aiding the integration of research approaches and techniques from these major fields. The editors, leading computer scientists from academia and industry, present a collection of 32 papers from contributors who are incorporating visualization and data mining techniques through academic research as well application development in industry and government agencies. Information Visualization focuses upon techniques to enhance the natural abilities of humans to visually understand data, in particular, large-scale data sets. It is primarily concerned with developing interactive graphical representations to enable users to more intuitively make sense of multidimensional data as part of the data exploration process. It includes research from computer science, psychology, human-computer interaction, statistics, and information science. Knowledge Discovery in Databases (KDD) most often refers to the process of mining databases for previously unknown patterns and trends in data. Data mining refers to the particular computational methods or algorithms used in this process. The data mining research field is most related to computational advances in database theory, artificial intelligence and machine learning. This work compiles research summaries from these main research areas in order to provide "a reference work containing the collection of thoughts and ideas of noted researchers from the fields of data mining and data visualization" (p. 8). It addresses these areas in three main sections: the first an data visualization, the second an KDD and model visualization, and the last an using visualization in the knowledge discovery process. The seven chapters of Part One focus upon methodologies and successful techniques from the field of Data Visualization. Hoffman and Grinstein (Chapter 2) give a particularly good overview of the field of data visualization and its potential application to data mining. An introduction to the terminology of data visualization, relation to perceptual and cognitive science, and discussion of the major visualization display techniques are presented. Discussion and illustration explain the usefulness and proper context of such data visualization techniques as scatter plots, 2D and 3D isosurfaces, glyphs, parallel coordinates, and radial coordinate visualizations. Remaining chapters present the need for standardization of visualization methods, discussion of user requirements in the development of tools, and examples of using information visualization in addressing research problems.
In 13 chapters, Part Two provides an introduction to KDD, an overview of data mining techniques, and examples of the usefulness of data model visualizations. The importance of visualization throughout the KDD process is stressed in many of the chapters. In particular, the need for measures of visualization effectiveness, benchmarking for identifying best practices, and the use of standardized sample data sets is convincingly presented. Many of the important data mining approaches are discussed in this complementary context. Cluster and outlier detection, classification techniques, and rule discovery algorithms are presented as the basic techniques common to the KDD process. The potential effectiveness of using visualization in the data modeling process are illustrated in chapters focused an using visualization for helping users understand the KDD process, ask questions and form hypotheses about their data, and evaluate the accuracy and veracity of their results. The 11 chapters of Part Three provide an overview of the KDD process and successful approaches to integrating KDD, data mining, and visualization in complementary domains. Rhodes (Chapter 21) begins this section with an excellent overview of the relation between the KDD process and data mining techniques. He states that the "primary goals of data mining are to describe the existing data and to predict the behavior or characteristics of future data of the same type" (p. 281). These goals are met by data mining tasks such as classification, regression, clustering, summarization, dependency modeling, and change or deviation detection. Subsequent chapters demonstrate how visualization can aid users in the interactive process of knowledge discovery by graphically representing the results from these iterative tasks. Finally, examples of the usefulness of integrating visualization and data mining tools in the domain of business, imagery and text mining, and massive data sets are provided. This text concludes with a thorough and useful 17-page index and lengthy yet integrating 17-page summary of the academic and industrial backgrounds of the contributing authors. A 16-page set of color inserts provide a better representation of the visualizations discussed, and a URL provided suggests that readers may view all the book's figures in color on-line, although as of this submission date it only provides access to a summary of the book and its contents. The overall contribution of this work is its focus an bridging two distinct areas of research, making it a valuable addition to the Morgan Kaufmann Series in Database Management Systems. The editors of this text have met their main goal of providing the first textbook integrating knowledge discovery, data mining, and visualization. Although it contributes greatly to our under- standing of the development and current state of the field, a major weakness of this text is that there is no concluding chapter to discuss the contributions of the sum of these contributed papers or give direction to possible future areas of research. "Integration of expertise between two different disciplines is a difficult process of communication and reeducation. Integrating data mining and visualization is particularly complex because each of these fields in itself must draw an a wide range of research experience" (p. 300). Although this work contributes to the crossdisciplinary communication needed to advance visualization in KDD, a more formal call for an interdisciplinary research agenda in a concluding chapter would have provided a more satisfying conclusion to a very good introductory text.

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Abstract

A modern information retrieval system must have the capability to find, organize and present very different manifestations of information - such as text, pictures, videos or database records - any of which may be of relevance to the user. However, the concept of relevance, while seemingly intuitive, is actually hard to define, and it's even harder to model in a formal way. Lavrenko does not attempt to bring forth a new definition of relevance, nor provide arguments as to why any particular definition might be theoretically superior or more complete. Instead, he takes a widely accepted, albeit somewhat conservative definition, makes several assumptions, and from them develops a new probabilistic model that explicitly captures that notion of relevance. With this book, he makes two major contributions to the field of information retrieval: first, a new way to look at topical relevance, complementing the two dominant models, i.e., the classical probabilistic model and the language modeling approach, and which explicitly combines documents, queries, and relevance in a single formalism; second, a new method for modeling exchangeable sequences of discrete random variables which does not make any structural assumptions about the data and which can also handle rare events. Thus his book is of major interest to researchers and graduate students in information retrieval who specialize in relevance modeling, ranking algorithms, and language modeling.

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Footnote

Diese Abschnitte sind verständlich geschrieben und trotz der mitunter gar nicht so einfachen Thematik auch für Einsteiger geeignet. Vorteilhaft ist sicherlich, dass die Autorin die Thesauruserstellung konsequent anhand eines einzelnen thematischen Beispiels demonstriert und dafür das Gebiet "animal welfare" gewählt hat, wohl nicht zuletzt auch deshalb, da die hier auftretenden Facetten und Beziehungen ohne allzu tiefgreifende fachwissenschaftliche Kenntnisse für die meisten Leser nachvollziehbar sind. Das methodische Gerüst der Facettenanalyse wird hier deutlich stärker betont als etwa in der (spärlichen) deutschsprachigen Thesaurusliteratur. Diese Vorgangsweise soll neben der Ordnungsbildung auch dazu verhelfen, die Zahl der Deskriptoren überschaubar zu halten und weniger auf komplexe (präkombinierte) Deskriptoren als auf postkoordinierte Indexierung zu setzen. Dafür wird im übrigen das als Verfeinerung der bekannten Ranganathanschen PMEST-Formel geltende Schema der 13 "fundamental categories" der UK Classification Research Group (CRG) vorgeschlagen bzw. in dem Beispiel verwendet (Thing / Kind / Part / Property; Material / Process / Operation; Patient / Product / By-product / Agent; Space; Time). Als "minor criticism" sei erwähnt, dass Broughton in ihrem Demonstrationsbeispiel als Notation für die erarbeitete Ordnung eine m.E. schwer lesbare Buchstabenfolge verwendet, obwohl sie zugesteht (S. 165), dass ein Zifferncode vielfach als einfacher handhabbar empfunden wird.

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Abstract

As information becomes more ubiquitous and the demands that searchers have on search systems grow, there is a need to support search behaviors beyond simple lookup. Information seeking is the process or activity of attempting to obtain information in both human and technological contexts. Exploratory search describes an information-seeking problem context that is open-ended, persistent, and multifaceted, and information-seeking processes that are opportunistic, iterative, and multitactical. Exploratory searchers aim to solve complex problems and develop enhanced mental capacities. Exploratory search systems support this through symbiotic human-machine relationships that provide guidance in exploring unfamiliar information landscapes. Exploratory search has gained prominence in recent years. There is an increased interest from the information retrieval, information science, and human-computer interaction communities in moving beyond the traditional turn-taking interaction model supported by major Web search engines, and toward support for human intelligence amplification and information use. In this lecture, we introduce exploratory search, relate it to relevant extant research, outline the features of exploratory search systems, discuss the evaluation of these systems, and suggest some future directions for supporting exploratory search. Exploratory search is a new frontier in the search domain and is becoming increasingly important in shaping our future world.

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Date

22. 3.2008 14:35:21

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Content

Inhalt: An Introduction to Metatheories, Theories, and Models (Marcia J. Bates) - What Methodology Does to Theory: Sense-Making Methodology as Exemplar (Brenda Dervin) Evolution in Information Behavior Modeling Wilson's Model (T.D. Wilson) - Affective Load (Diane Nahl) - Anomalous State of Knowledge (Nicholas J. Belkin) - Archival Intelligence (Elizabeth Yakel) - Bandura's Social Cognition (Makiko Miwa) - Berrypicking (Marcia J. Bates) - Big6 Skills for Information Literacy (Carrie A. Lowe and Michael B. Eisenberg) - Chang's Browsing (Chan-Ju L. Chang) - Chatman's Information Poverty (Julie Hersberger) - Chatman's Life in the Round (Crystal Fulton) - Cognitive Authority (Soo Young Rieh) - Cognitive Work Analysis (Raya Fidel and Annelise Mark Pejtersen) - Collective Action Dilemma (Marc Smith and Howard T. Weiser) - Communicative Action (Gerald Benoît) - Communities of Practice (Elisabeth Davies) - Cultural Models of Hall and Hofstede (Anita Komlodi) - Dervin's Sense-Making (Tonyia J. Tidline) - Diffusion Theory (Darian Lajoie-Paquette) - The Domain Analytic Approach to Scholars' Information Practices (Sanna Talja) - Ecological Theory of Human Information Behavior (Kirsty Williamson) - Elicitation as Micro-Level Information Seeking (Mei-Mei Wu) - Ellis's Model of InformationSeeking Behavior (David Ellis) - Everyday Life Information Seeking (Reijo Savolainen) - Face Threat (Lorri Mon) - Flow Theory (Charles Naumer) - General Model of the Information Seeking of Professionals (Gloria J. Leckie) - The Imposed Query (Melissa Gross) - Information Acquiringand-Sharing (Kevin Rioux) - Information Activities in Work Tasks (Katriina Byström) - Information Encountering (Sanda Erdelez) - Information Grounds (Karen E. Fisher) - Information Horizons (Diane H. Sonnenwald) - Information Intents (Ross J. Todd) - Information Interchange (Rita Marcella and Graeme Baxter) - Institutional Ethnography (Roz Stooke) - Integrative Framework for Information Seeking and Interactive Information Retrieval (Peter Ingwersen) - Interpretative Repertoires (Pamela J. McKenzie) - Krikelas's Model of Information Seeking (Jean Henefer and Crystal Fulton) - Kuhlthau's Information Search Process (Carol Collier Kuhlthau) - Library Anxiety (Patricia Katopol) - Monitoring and Blunting (Lynda M. Baker) - Motivational Factors for Interface Design (Carolyn Watters and Jack Duffy) - Network Gatekeeping (Karine Barzilai-Nahon) - Nonlinear Information Seeking (Allen Foster) - Optimal Foraging (JoAnn Jacoby) - Organizational Sense Making and Information Use (Anu Maclntosh-Murray) - The PAIN Hypothesis (Harry Bruce) -
Perspectives on the Tasks in which Information Behaviors Are Embedded (Barbara M. Wildemuth and Anthony Hughes) - Phenomenography (Louise Limberg) - Practice of Everyday Life (Paulette Rothbauer) - Principle of Least Effort (Donald O. Case) - Professions and Occupational Identities (Olof Sundin and Jenny Hedman) - Radical Change (Eliza T. Dresang) - Reader Response Theory (Catherine Sheldrick Ross) - Rounding and Dissonant Grounds (Paul Solomon) - Serious Leisure (Jenna Hartel) - Small-World Network Exploration (Lennart Björneborn) - Nan Lin's Theory of Social Capital (Catherine A. Johnson) - The Social Constructionist Viewpoint on Information Practices (Kimmo Tuominen, Sanna Talja, and Reijo Savolainen) - Social Positioning (Lisa M. Given) - The Socio-Cognitive Theory of Users Situated in Specific Contexts and Domains (Birger Hjoerland) - Strength of Weak Ties (Christopher M. Dixon) - Symbolic Violence (Steven Joyce) - Taylor's Information Use Environments (Ruth A. Palmquist) - Taylor's Question-Negotiation (Phillip M. Edwards) - Transtheoretical Model of the Health Behavior Change (C. Nadine Wathen and Roma M. Harris) - Value Sensitive Design (Batya Friedman and Nathan G. Freier) - Vygotsky's Zone of Proximal Development (Lynne (E. E) McKechnie) - Web Information Behaviors of Organizational Workers (Brian Detlor) - Willingness to Return (Tammara Combs Turner and Joan C. Durrance) - Women's Ways of Knowing (Heidi Julien) - Work Task Information-Seeking and Retrieval Processes (Preben Hansen) - World Wide Web Information Seeking (Don Turnbull)

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Date

22. 3.2008 14:29:25

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Date

22. 3.2008 16:15:37

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Classification

006.7 22

Date

7. 3.2007 19:30:22

DDC

006.7 22

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Abstract

Human beings are information omnivores: we are constantly collecting, labeling, and organizing data. But today, the shift from the physical to the digital is mixing, burning, and ripping our lives apart. In the past, everything had its one place--the physical world demanded it--but now everything has its places: multiple categories, multiple shelves. Simply put, everything is suddenly miscellaneous. In Everything Is Miscellaneous, David Weinberger charts the new principles of digital order that are remaking business, education, politics, science, and culture. In his rollicking tour of the rise of the miscellaneous, he examines why the Dewey decimal system is stretched to the breaking point, how Rand McNally decides what information not to include in a physical map (and why Google Earth is winning that battle), how Staples stores emulate online shopping to increase sales, why your children's teachers will stop having them memorize facts, and how the shift to digital music stands as the model for the future in virtually every industry. Finally, he shows how by "going miscellaneous," anyone can reap rewards from the deluge of information in modern work and life. From A to Z, Everything Is Miscellaneous will completely reshape the way you think--and what you know--about the world.

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Date

22. 3.2008 18:05:16

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