In the eye-blink that has elapsed since the turn of the millennium, the lives of those of us who work with information have been utterly transformed. Pretty well all we need to know is on the web; if not today, then tomorrow. It's where we learn and play, shop and do business, keep up with old friends and meet new ones. What makes it possible for us to find the stuff we need to know? Search engines.
Search engines - "web dragons" - are the portals through which we access society's treasure trove of information. How do they stack up against librarians, the gatekeepers over centuries past? What role will libraries play in a world whose information is ruled by the web? How is the web organized? Who controls its contents, and how do they do it? How do search engines work? How can web visibility be exploited by those who want to sell us their wares? What's coming tomorrow, and can we influence it? We are witnessing the dawn of a new era, starting right now - and this book shows you what it will look like and how it will change your world.
Do you use search engines every day? Are you a developer or a librarian, helping others with their information needs? A researcher or journalist for whom the web has changed the very way you work? An online marketer or site designer, whose career exists because of the web? Whoever you are: if you care about information, this book will open your eyes - and make you blink.
About the authors:
Ian H. Witten is professor of computer science at the University of Waikato, where he directs the New Zealand Digital Library research project. He has published widely on digital libraries, machine learning, text compression, hypertext, speech synthesis and signal processing, and computer typography. A fellow of the ACM, he has written several books, including How to Build a Digital Library (2002) and Data Mining (2005), both from Morgan Kaufmann.
Marco Gori is professor of computer science at the University of Siena, where he leads the artificial intelligence research group. He is the Chairman of the Italian Chapter of the IEEE Computational Intelligence Society, a fellow of the IEEE and of the ECCAI, and former President of the Italian Association for Artificial Intelligence.
Teresa Numerico teaches network theory and communication studies at the University of Rome 3, and is a researcher in Philosophy of Science at the University of Salerno. Previously she was employed as a business development and marketing manager for various media companies, including the Italian branch of Turner Broadcasting System (CNN and Cartoon Network).
* Presents a critical view of the idea of funneling information access through a small handful of gateways and the notion of a centralized index--and the problems that may cause.
* Provides promising approaches for addressing the problems, such as the personalization of web services.
* Presented by authorities in the field of digital libraries, web history, machine learning, and web and data mining.
* Find more information at the author's site: webdragons.net.

A complete lexicon of technical information, the Dictionary of Computer Science, Engineering, and Technology provides workable definitions, practical information, and enhances general computer science and engineering literacy. It spans various disciplines and industry sectors such as: telecommunications, information theory, and software and hardware systems. If you work with, or write about computers, this dictionary is the single most important resource you can put on your shelf.
The dictionary addresses all aspects of computing and computer technology from multiple perspectives, including the academic, applied, and professional vantage points. Including more than 8,000 terms, it covers all major topics from artificial intelligence to programming languages, from software engineering to operating systems, and from database management to privacy issues. The definitions provided are detailed rather than concise.
Written by an international team of over 80 contributors, this is the most comprehensive and easy-to-read reference of its kind. If you need to know the definition of anything related to computers you will find it in the Dictionary of Computer Science, Engineering, and Technology.

This book is devoted to adaptive processing of structured information similar to flexible and intelligent information processing by humans - in contrast to merely sequential processing of predominantly symbolic information within a deterministic framework. Adaptive information processing allows for a mixture of sequential and parallel processing of symbolic as well as subsymbolic information within deterministic and probabilistic frameworks.
The book originates from a summer school held in September 1997 and thus is ideally suited for advanced courses on adaptive information processing and advanced learning techniques or for self-instruction. Research and design professionals active in the area of neural information processing will find it a valuable state-of-the-art survey.

This book presents the refereed proceedings of the 4th Congress of the Italian Association for Artificial Intelligence, AI*IA '95, held in Florence, Italy, in October 1995.
The 31 revised full papers and the 12 short presentations contained in the volume were selected from a total of 101 submissions on the basis of a careful reviewing process. The papers are organized in sections on natural language processing, fuzzy systems, machine learning, knowledge representation, automated reasoning, cognitive models, robotics and planning, connectionist models, model-based reasoning, and distributed artificial intelligence.

The remarkable progress in computer vision over the last few years is, by and large, attributed to deep learning, fueled by the availability of huge sets of labeled data, and paired with the explosive growth of the GPU paradigm. While subscribing to this view, this work criticizes the supposed scientific progress in the field, and proposes the investigation of vision within the framework of information-based laws of nature. This work poses fundamental questions about vision that remain far from understood, leading the reader on a journey populated by novel challenges resonating with the foundations of machine learning. The central thesis proposed is that for a deeper understanding of visual computational processes, it is necessary to look beyond the applications of general purpose machine learning algorithms, and focus instead on appropriate learning theories that take into account the spatiotemporal nature of the visual signal. Serving to inspire and stimulate critical reflection and discussion, yet requiring no prior advanced technical knowledge, the text can naturally be paired with classic textbooks on computer vision to better frame the current state of the art, open problems, and novel potential solutions. As such, it will be of great benefit to graduate and advanced undergraduate students in computer science, computational neuroscience, physics, and other related disciplines.