Search (27 results, page 2 of 2)

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Abstract

From classification to knowledge organization through subject indexing the field has been so rapidly growing that it is difficult to demarcate its boundaries. Knowledge organization is viewed in the sense of conglomeration of activities to sort and order knowledge, to acquire, ufilize, evaluate, represent and communicate knowledge for problem solving. It has been no simple matter to decide what should be included in and excluded from such a dictionary. Broadly speaking the terms an the following topics are included in the work : Knowledge, Epistemology, Concepts, Terminology and Vocabulary control ; Classification systems, their design, theory and practice of classification, Subject analysis; fundamental categories and facets, Content and Text analysis, Use of classification in online systems and an the web. Subject cataloguing : subject headings, Thesauri and alphabetical indexing languages : Keyword, chain and string indexes, Knowledge representation, Classification for access and retrieval, Cognitive aspects of information- seeking behaviour, Automatic classification, Descriptive cataloguing : Theory, kinds, levels, standards and codes, OPACs, all are covered in this work. Like any other such work of this sort, it is an electic compilation. The work proposes to be descriptive rather than prescriptive. Endeavour is to find brief simple, logical and consensual meaning of terms, and append brief description of a concept or an issue with explanation, examples and comments in a bottom up way. Some current topics denoted by phrases have also been included. At times it may give the look of a concise encyclopaedic dictionary. Terms fully describe concepts and methods, and may evoke some thoughts an current and classic issues in the field.

Footnote

Rez. in: Knowledge organization 31(2004) no.3, S.196-198 (M. Hudon)

Pages

248 S

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Content

Inhalt: A Introduction of Universal Decimal Classification B Notational System in Number Building of UDC C Internal Structure of UDC for Number Building D Practical Classification and Number Building in UDC 0 Generalities 1. Philosophy. Metaphysics 2. Religion. Theology 3. Social Sciences 4. Philology. Linguistics 5. Mathematics and Natural Science 6. Applied Sciences. Medicine & Technology 7. The arts. Recreation Entertainment. Sport 8. Literature Belles- Letters 9. Geography. Biography. History Model Test Analysis Things to do--- Test No. 1-9

Pages

266 S

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Abstract

This revised edition of Wynar's Introduction to Cataloging and Classification (9th ed., 2000) completely incorporates revisions of AACR2, enhancements to MARC 21, and developments in areas such as resource description and access. Aside from the many revisions and updates and improved organization, the basic content remains the same. Beginning with an introduction to cataloging, cataloging rules, and MARC format, the book then turns to its largest section, "Description and Access." Authority control is explained, and the various methods of subject access are described in detail. Finally, administrative issues, including catalog management, are discussed. The glossary, source notes, suggested reading, and selected bibliography have been updated and expanded, as has the index. The examples throughout help to illustrate rules and concepts, and most MARC record examples are now shown in OCLC's Connexion format. This is an invaluable resource for cataloging students and beginning catalogers as well as a handy reference tool for more experienced catalogers.

Footnote

Rez. in: Reference and user services quarterly 46(2007) no.3, S.104-105 (C.N. Conway); Technicalities 27(2007) no.2, S.19-20 (S.S. Intner)

Pages

xviii, 589 S

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Footnote

Vgl. auch: Patton, G.E.: From FRBR to FRAD: extending the Model. In: http://www.ifla.org/files/hq/papers/ifla75/215-patton-en.pdf.

Pages

101 S

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Abstract

Why doesn't your home page appear on the first page of search results, even when you query your own name? How do other Web pages always appear at the top? What creates these powerful rankings? And how? The first book ever about the science of Web page rankings, "Google's PageRank and Beyond" supplies the answers to these and other questions and more. The book serves two very different audiences: the curious science reader and the technical computational reader. The chapters build in mathematical sophistication, so that the first five are accessible to the general academic reader. While other chapters are much more mathematical in nature, each one contains something for both audiences. For example, the authors include entertaining asides such as how search engines make money and how the Great Firewall of China influences research. The book includes an extensive background chapter designed to help readers learn more about the mathematics of search engines, and it contains several MATLAB codes and links to sample Web data sets. The philosophy throughout is to encourage readers to experiment with the ideas and algorithms in the text. Any business seriously interested in improving its rankings in the major search engines can benefit from the clear examples, sample code, and list of resources provided. It includes: many illustrative examples and entertaining asides; MATLAB code; accessible and informal style; and complete and self-contained section for mathematics review.

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

Pages

X, 224 S

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Pages

VIII, 524 S

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Pages

XIII, 283 S