Search (19 results, page 1 of 1)

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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.

Classification

ST 270 Informatik / Monographien / Software und -entwicklung / Datenbanken, Datenbanksysteme, Data base management, Informationssysteme

LCSH

Data mining ; Information retrieval
Data mining / Congresses (GBV)

RVK

ST 270 Informatik / Monographien / Software und -entwicklung / Datenbanken, Datenbanksysteme, Data base management, Informationssysteme

Subject

Data mining ; Information retrieval
Data mining / Congresses (GBV)

Theme

Data Mining

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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.
With contributors almost exclusively from the computer science field, the intended audience of this work is heavily slanted towards a computer science perspective. However, it is highly readable and provides introductory material that would be useful to information scientists from a variety of domains. Yet, much interesting work in information visualization from other fields could have been included giving the work more of an interdisciplinary perspective to complement their goals of integrating work in this area. Unfortunately, many of the application chapters are these, shallow, and lack complementary illustrations of visualization techniques or user interfaces used. However, they do provide insight into the many applications being developed in this rapidly expanding field. The authors have successfully put together a highly useful reference text for the data mining and information visualization communities. Those interested in a good introduction and overview of complementary research areas in these fields will be satisfied with this collection of papers. The focus upon integrating data visualization with data mining complements texts in each of these fields, such as Advances in Knowledge Discovery and Data Mining (Fayyad et al., MIT Press) and Readings in Information Visualization: Using Vision to Think (Card et. al., Morgan Kauffman). This unique work is a good starting point for future interaction between researchers in the fields of data visualization and data mining and makes a good accompaniment for a course focused an integrating these areas or to the main reference texts in these fields."

LCSH

Data mining

RSWK

Visualisierung / Computergraphik / Data Mining
Data Mining / Visualisierung / Aufsatzsammlung (BVB)

Series

Morgan Kaufmann series in data management systems

Subject

Visualisierung / Computergraphik / Data Mining
Data Mining / Visualisierung / Aufsatzsammlung (BVB)
Data mining

Theme

Data Mining

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Abstract

Interested in how an efficient search engine works? Want to know what algorithms are used to rank resulting documents in response to user requests? The authors answer these and other key information on retrieval design and implementation questions is provided. This book is not yet another high level text. Instead, algorithms are thoroughly described, making this book ideally suited for both computer science students and practitioners who work on search-related applications. As stated in the foreword, this book provides a current, broad, and detailed overview of the field and is the only one that does so. Examples are used throughout to illustrate the algorithms. The authors explain how a query is ranked against a document collection using either a single or a combination of retrieval strategies, and how an assortment of utilities are integrated into the query processing scheme to improve these rankings. Methods for building and compressing text indexes, querying and retrieving documents in multiple languages, and using parallel or distributed processing to expedite the search are likewise described. This edition is a major expansion of the one published in 1998. Neuaufl. 2005: Besides updating the entire book with current techniques, it includes new sections on language models, cross-language information retrieval, peer-to-peer processing, XML search, mediators, and duplicate document detection.

Classification

ST 270 Informatik / Monographien / Software und -entwicklung / Datenbanken, Datenbanksysteme, Data base management, Informationssysteme

RVK

ST 270 Informatik / Monographien / Software und -entwicklung / Datenbanken, Datenbanksysteme, Data base management, Informationssysteme

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Abstract

The second edition of Understanding Search Engines: Mathematical Modeling and Text Retrieval follows the basic premise of the first edition by discussing many of the key design issues for building search engines and emphasizing the important role that applied mathematics can play in improving information retrieval. The authors discuss important data structures, algorithms, and software as well as user-centered issues such as interfaces, manual indexing, and document preparation. Significant changes bring the text up to date on current information retrieval methods: for example the addition of a new chapter on link-structure algorithms used in search engines such as Google. The chapter on user interface has been rewritten to specifically focus on search engine usability. In addition the authors have added new recommendations for further reading and expanded the bibliography, and have updated and streamlined the index to make it more reader friendly.

LCSH

Text processing (Computer science)

Subject

Text processing (Computer science)

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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
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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Abstract

As the World Wide Web continues to expand, it becomes increasingly difficult for users to obtain information efficiently. Because most search engines read format languages such as HTML or SGML, search results reflect formatting tags more than actual page content, which is expressed in natural language. Spinning the Semantic Web describes an exciting new type of hierarchy and standardization that will replace the current "Web of links" with a "Web of meaning." Using a flexible set of languages and tools, the Semantic Web will make all available information - display elements, metadata, services, images, and especially content - accessible. The result will be an immense repository of information accessible for a wide range of new applications. This first handbook for the Semantic Web covers, among other topics, software agents that can negotiate and collect information, markup languages that can tag many more types of information in a document, and knowledge systems that enable machines to read Web pages and determine their reliability. The truly interdisciplinary Semantic Web combines aspects of artificial intelligence, markup languages, natural language processing, information retrieval, knowledge representation, intelligent agents, and databases.

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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Classification

006.7 22

Date

7. 3.2007 19:30:22

DDC

006.7 22

Footnote

The final part of the book discusses research in multimedia content management systems and the semantic web, and presents examples and applications for semantic multimedia analysis in search and retrieval systems. These chapters describe example systems in which current projects have been implemented, and include extensive results and real demonstrations. For example, real case scenarios such as ECommerce medical applications and Web services have been introduced. Topics in natural language, speech and image processing techniques and their application for multimedia indexing, and content-based retrieval have been elaborated upon with extensive examples and deployment methods. The editors of the book themselves provide the readers with a chapter about their latest research results on knowledge-based multimedia content indexing and retrieval. Some interesting applications for multimedia content and the semantic web are introduced. Applications that have taken advantage of the metadata provided by MPEG7 in order to realize advance-access services for multimedia content have been provided. The applications discussed in the third part of the book provide useful guidance to researchers and practitioners properly planning to implement semantic multimedia analysis techniques in new research and development projects in both academia and industry. A fourth part should be added to this book: performance measurements for integrated approaches of multimedia analysis and the semantic web. Performance of the semantic approach is a very sophisticated issue and requires extensive elaboration and effort. Measuring the semantic search is an ongoing research area; several chapters concerning performance measurement and analysis would be required to adequately cover this area and introduce it to readers."

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Abstract

A practical approach to developing and operating an effective programme to manage hybrid records within an organization. This title positions records management as an integral business function linked to the organisation's business aims and objectives. The authors also address the records requirements of new and significant pieces of legislation, such as data protection and freedom of information, as well as exploring strategies for managing electronic records. Bullet points, checklists and examples assist the reader throughout, making this a one-stop resource for information in this area.

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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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LCSH

Document Preparation and Text Processing

Subject

Document Preparation and Text Processing

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Series

Advanced information and knowledge processing

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Abstract

Libraries have always been an inspiration for the standards and technologies developed by semantic web activities. However, except for the Dublin Core specification, semantic web and social networking technologies have not been widely adopted and further developed by major digital library initiatives and projects. Yet semantic technologies offer a new level of flexibility, interoperability, and relationships for digital repositories. Kruk and McDaniel present semantic web-related aspects of current digital library activities, and introduce their functionality; they show examples ranging from general architectural descriptions to detailed usages of specific ontologies, and thus stimulate the awareness of researchers, engineers, and potential users of those technologies. Their presentation is completed by chapters on existing prototype systems such as JeromeDL, BRICKS, and Greenstone, as well as a look into the possible future of semantic digital libraries. This book is aimed at researchers and graduate students in areas like digital libraries, the semantic web, social networks, and information retrieval. This audience will benefit from detailed descriptions of both today's possibilities and also the shortcomings of applying semantic web technologies to large digital repositories of often unstructured data.

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Abstract

The Text REtrieval Conference (TREC), a yearly workshop hosted by the US government's National Institute of Standards and Technology, provides the infrastructure necessary for large-scale evaluation of text retrieval methodologies. With the goal of accelerating research in this area, TREC created the first large test collections of full-text documents and standardized retrieval evaluation. The impact has been significant; since TREC's beginning in 1992, retrieval effectiveness has approximately doubled. TREC has built a variety of large test collections, including collections for such specialized retrieval tasks as cross-language retrieval and retrieval of speech. Moreover, TREC has accelerated the transfer of research ideas into commercial systems, as demonstrated in the number of retrieval techniques developed in TREC that are now used in Web search engines. This book provides a comprehensive review of TREC research, summarizing the variety of TREC results, documenting the best practices in experimental information retrieval, and suggesting areas for further research. The first part of the book describes TREC's history, test collections, and retrieval methodology. Next, the book provides "track" reports -- describing the evaluations of specific tasks, including routing and filtering, interactive retrieval, and retrieving noisy text. The final part of the book offers perspectives on TREC from such participants as Microsoft Research, University of Massachusetts, Cornell University, University of Waterloo, City University of New York, and IBM. The book will be of interest to researchers in information retrieval and related technologies, including natural language processing.

LCSH

Text processing (Computer science) / Congresses

Subject

Text processing (Computer science) / Congresses

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Classification

ST 270 [Informatik # Monographien # Software und -entwicklung # Datenbanken, Datenbanksysteme, Data base management, Informationssysteme]

RVK

ST 270 [Informatik # Monographien # Software und -entwicklung # Datenbanken, Datenbanksysteme, Data base management, Informationssysteme]

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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 14:29:25

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Abstract

In this collection of nearly 50 articles written by librarians, computer specialists, and other information professionals, the reader finds 10 chapters, each devoted to a problem or a side effect that has emerged since the introduction of the Internet: control over selection, survival of the book, training users, adapting to users' expectations, access issues, cost of technology, continuous retraining, legal issues, disappearing data, and how to avoid becoming blind sided. After stating a problem, each chapter offers solutions that are subsequently supported by articles. The editor's comments, which appear throughout the text, are an added bonus, as are the sections concluding the book, among them a listing of useful URLs, a works-cited section, and a comprehensive index. This book has much to recommend it, especially the articles, which are not only informative, thought-provoking, and interesting but highly readable and accessible as well. An indispensable tool for all librarians.

Footnote

Unlike muck of the professional library literature, Net Effects is not an open-aimed embrace of technology. Block even suggests that it is helpful to have a Luddite or two an each library staff to identify the setbacks associated with technological advances in the library. Each of the book's 10 chapters deals with one Internet-related problem, such as "Chapter 4-The Shifted Librarian: Adapting to the Changing Expectations of Our Wired (and Wireless) Users," or "Chapter 8-Up to Our Ears in Lawyers: Legal Issues Posed by the Net." For each of these 10 problems, multiple solutions are offered. For example, for "Chapter 9-Disappearing Data," four solutions are offered. These include "Link-checking," "Have a technological disaster plan," "Advise legislators an the impact proposed laws will have," and "Standards for preservation of digital information." One article is given to explicate each of these four solutions. A short bibliography of recommended further reading is also included for each chapter. Block provides a short introduction to each chapter, and she comments an many of the entries. Some of these comments seem to be intended to provide a research basis for the proposed solutions, but they tend to be vague generalizations without citations, such as, "We know from research that students would rather ask each other for help than go to adults. We can use that (p. 91 )." The original publication dates of the entries range from 1997 to 2002, with the bulk falling into the 2000-2002 range. At up to 6 years old, some of the articles seem outdated, such as a 2000 news brief announcing the creation of the first "customizable" public library Web site (www.brarydog.net). These critiques are not intended to dismiss the volume entirely. Some of the entries are likely to find receptive audiences, such as a nuts-and-bolts instructive article for making Web sites accessible to people with disabilities. "Providing Equitable Access," by Cheryl H. Kirkpatrick and Catherine Buck Morgan, offers very specific instructions, such as how to renovate OPAL workstations to suit users with "a wide range of functional impairments." It also includes a useful list of 15 things to do to make a Web site readable to most people with disabilities, such as, "You can use empty (alt) tags (alt="') for images that serve a purely decorative function. Screen readers will skip empty (alt) tags" (p. 157). Information at this level of specificity can be helpful to those who are faced with creating a technological solution for which they lack sufficient technical knowledge or training.

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