Search (4 results, page 1 of 1)

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Date

22. 3.2008 14:24:08

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Abstract

The World Wide Web is rapidly filling with more text than anyone could have imagined even a short time ago, but the task of isolating relevant parts of this vast information has become just that much more daunting. Richard Belew brings a cognitive perspective to the study of information retrieval as a discipline within computer science. He introduces the idea of Finding Out About (FDA) as the process of actively seeking out information relevant to a topic of interest and describes its many facets - ranging from creating a good characterization of what the user seeks, to what documents actually mean, to methods of inferring semantic clues about each document, to the problem of evaluating whether our search engines are performing as we have intended. Finding Out About explains how to build the tools that are useful for searching collections of text and other media. In the process it takes a close look at the properties of textual documents that do not become clear until very large collections of them are brought together and shows that the construction of effective search engines requires knowledge of the statistical and mathematical properties of linguistic phenomena, as well as an appreciation for the cognitive foundation we bring to the task as language users. The unique approach of this book is its even handling of the phenomena of both numbers and words, making it accessible to a wide audience. The textbook is usable in both undergraduate and graduate classes on information retrieval, library science, and computational linguistics. The text is accompanied by a CD-ROM that contains a hypertext version of the book, including additional topics and notes not present in the printed edition. In addition, the CD contains the full text of C.J. "Keith" van Rijsbergen's famous textbook, Information Retrieval (now out of print). Many active links from Belew's to van Rijsbergen's hypertexts help to unite the material. Several test corpora and indexing tools are provided, to support the design of your own search engine. Additional exercises using these corpora and code are available to instructors. Also supporting this book is a Web site that will include recent additions to the book, as well as links to sites of new topics and methods.

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Content

Inhalt: Tim Bemers-Lee: The Original Dream - Re-enter Machines - Where Are We Now? - The World Wide Web Consortium - Where Is the Web Going Next? / Dieter Fensel, James Hendler, Henry Lieberman, and Wolfgang Wahlster: Why Is There a Need for the Semantic Web and What Will It Provide? - How the Semantic Web Will Be Possible / Jeff Heflin, James Hendler, and Sean Luke: SHOE: A Blueprint for the Semantic Web / Deborah L. McGuinness, Richard Fikes, Lynn Andrea Stein, and James Hendler: DAML-ONT: An Ontology Language for the Semantic Web / Michel Klein, Jeen Broekstra, Dieter Fensel, Frank van Harmelen, and Ian Horrocks: Ontologies and Schema Languages on the Web / Borys Omelayenko, Monica Crubezy, Dieter Fensel, Richard Benjamins, Bob Wielinga, Enrico Motta, Mark Musen, and Ying Ding: UPML: The Language and Tool Support for Making the Semantic Web Alive / Deborah L. McGuinness: Ontologies Come of Age / Jeen Broekstra, Arjohn Kampman, and Frank van Harmelen: Sesame: An Architecture for Storing and Querying RDF Data and Schema Information / Rob Jasper and Mike Uschold: Enabling Task-Centered Knowledge Support through Semantic Markup / Yolanda Gil: Knowledge Mobility: Semantics for the Web as a White Knight for Knowledge-Based Systems / Sanjeev Thacker, Amit Sheth, and Shuchi Patel: Complex Relationships for the Semantic Web / Alexander Maedche, Steffen Staab, Nenad Stojanovic, Rudi Studer, and York Sure: SEmantic portAL: The SEAL Approach / Ora Lassila and Mark Adler: Semantic Gadgets: Ubiquitous Computing Meets the Semantic Web / Christopher Frye, Mike Plusch, and Henry Lieberman: Static and Dynamic Semantics of the Web / Masahiro Hori: Semantic Annotation for Web Content Adaptation / Austin Tate, Jeff Dalton, John Levine, and Alex Nixon: Task-Achieving Agents on the World Wide Web

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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

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