Search (2 results, page 1 of 1)

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Abstract

Für Webseiten ist, wie für alle interaktiven Anwendungen vom einfachen Automaten bis zur komplexen Software, die Benutzerfreundlichkeit von zentraler Bedeutung. Allerdings wird eine sinnvolle Benutzung von Informationsangeboten im World Wide Web häufig durch "cooles Design" unnötig erschwert, weil zentrale Punkte der Benutzerfreundlichkeit (Usability) vernachlässigt werden. Durch Usability Evaluation kann die Benutzerfreundlichkeit von Webseiten und damit auch die Akzeptanz bei den Benutzern verbessert werden. Ziel ist die Gestaltung von ansprechenden benutzerfreundlichen Webangeboten, die den Benutzern einen effektiven und effizienten Dialog ermöglichen. Das Buch bietet eine praxisorientierte Einführung in die Web Usability Evaluation und beschreibt die Anwendung ihrer verschiedenen Methoden.

Classification

ST 252 Informatik / Monographien / Software und -entwicklung / Web-Programmierung, allgemein
AP 15860 Allgemeines / Medien- und Kommunikationswissenschaften, Kommunikationsdesign / Formen der Kommunikation und des Kommunikationsdesigns / Kommunikationsdesign in elektronischen Medien

Content

Einführung.- Grundlagen des Web-Designs.- Usability und Usability Engineering.- Usability Engineering und das Web.- Methodenfragen zur Usability Evaluation.Expertenorientierte Methoden.- Benutzerorientierte Methoden.- Suchmaschinenorientierte Methoden.- Literatur.Glossar.- Index.- Checklisten.

Date

22. 3.2008 14:24:08

RVK

ST 252 Informatik / Monographien / Software und -entwicklung / Web-Programmierung, allgemein
AP 15860 Allgemeines / Medien- und Kommunikationswissenschaften, Kommunikationsdesign / Formen der Kommunikation und des Kommunikationsdesigns / Kommunikationsdesign in elektronischen Medien

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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