A number of approaches have been advanced for taking data about a user's likes and dislikes and generating a general profile of the user. These profiles can be used to retrieve documents matching user interests; recommend music, movies, or other similar products; or carry out other tasks in a specialized fashion. This article presents a fundamentally new method for generating user profiles that takes advantage of a large-scale database of demographic data. These data are used to generalize user-specified data along the patterns common across the population, including areas not represented in the user's original data. I describe the method in detail and present its implementation in the LIFESTYLE FINDER agent, an internet-based experiment testing our approach on more than 20,006 users worldwide.

The difficulty of finding information on the World Wide Web by browsing hypertext documents has led to the development and deployment of various search engines and indexing techniques. However, many information-gathering tasks are better handled by finding a referral to a human expert rather than by simply interacting with online information sources. A personal referral allows a user to judge the quality of the information he or she is receiving as well as to potentially obtain information that is deliberately not made public. The process of finding an expert who is both reliable and likely to respond to the user can be viewed as a search through the net-work of social relationships between individuals as opposed to a search through the network of hypertext documents. The goal of the REFERRAL WEB Project is to create models of social networks by data mining the web and develop tools that use the models to assist in locating experts and related information search and evaluation tasks.

I view the World Wide Web as an information food chain. The maze of pages and hyperlinks that comprise the Web are at the very bottom of the chain. The WEBCRAWLERs and ALTAVISTAs of the world are information herbivores; they graze on Web pages and regurgitate them as searchable indices. Today, most Web users feed near the bottom of the information food chain, but the time is ripe to move up. Since 1991, we have been building information carnivores, which intelligently hunt and feast on herbivores in UNIX, on the Internet, and on the Web. Information carnivores will become increasingly critical as the Web continues to grow and as more naive users are exposed to its chaotic jumble.

This article describes FAQ FINDER, a natural language question-answering system that uses files of frequently asked questions as its knowledge base. Unlike AI question-answering systems that focus on the generation of new answers, FAQ FINDER retrieves existing ones found in frequently asked question files. Unlike information-retrieval approaches that rely on a purely lexical metric of similarity between query and document, FAQ FINDER uses a semantic knowledge base (WORDNET) to improve its ability to match question and answer. We include results from an evaluation of the system's performance and show that a combination of semantic and statistical techniques works better than any single approach.

The mail sorting, folding, and inserting mobile personal communications goal is to facilitate the design of exhaust equipment, has implemented an expert network that will permit any mufflers of inlet manifolds in system solution at the core of its type of wireless telephone transmission--voice, hours instead of days. Air Force Manufacturing Technology service data from which common GKIS Intelligent Systems (Houston, Directorate (MANTECH) (Wright-Patterson knowledge--such as service procedures, Tex.) has developed the It is process to prove out and select Intergraph (Huntsville, Ala.), a designed to mine environmental optimal new concepts. The company has Industries (Phenix City, Ala.), a decisions related to advanced launched Project Solomon to upgrade textile manufacturer, is using an automated strike-warfare technology. The Workers' Compensation Fund uses advanced vision technology, neural knowledge-based software. The system compares workers' to develop a fuzzy logic-based solution off-quality production.

Behind were maneuvering through an officelike The Fourteenth National Conference the playing lies years of research in environment, getting from one on Artificial Intelligence (AAAI-97) imbuing machines with the intelligence location to another. Then the tasks and the Ninth Conference on Innovative to plan strategies based on a became more complex as they had to Applications of Artificial Intelligence changing environment. The implications find an object, for example, and transport (IAAI-97) will be held in of such problem-solving abilities it from point A to point B. Providence, Rhode Island, from 27-lie far beyond the game board, Now the events are becoming 31 July 1997. The Third International and the programs' authors will be on more closely linked to real-world Conference on Knowledge Discovery hand to discuss the technical and social tasks. There are four events this year.

Search engines are among the most successful applications on the web today. So many search engines have been created that it is difficult for users to know where they are, how to use them, and what topics they best address. Metasearch engines reduce the user burden by dispatching queries to multiple search engines in parallel. The SAVVYSEARCH metasearch engine is designed to efficiently query other search engines by carefully selecting those search engines likely to return useful results and responding to fluctuating load demands on the web. SAVVYSEARCH learns to identify which search engines are most appropriate for particular queries, reasons about resource demands, and represents an iterative parallel search strategy as a simple plan.

Date: 4/1/2002 WASA -- World Aeronautics & Space Administration Executive Summary of Committee Report on Disaster Investigation, Incident # 362 Analysis of records downloaded from the 2001 Jupiter Orbital Black Parallelopiped Investigation Mission indicates that the basic source of failure was excessive emotional stress in the HAL computer, leading to a previously unknown condition now called Computational Paranoia. This in turn was an unforeseen side-effect of the design of the HAL-9000 series. HAL was given a genuine personality, enabling it to act as an onboard psychiatric advisor, colleague, and confidante to the human crew members. As a consequence, much of HAL's perceptual software was devoted to reading subtleties of facial expression, unconscious intonation stresses, and other emotional signals. Its performance at empathy and emotional insight was at least two orders of magnitude (as measured by the Kraft-Ebbing-Rachmaninoff method) better than that of the rest of the crew.

Some people believe that the expert system field is dead, yet others believe it is alive and well. To gain a better insight into these possible views, the first three world congresses on expert systems (which typically attract representatives from some 45-50 countries) are used to determine the health of the global expert system field in terms of applied technologies, applications, and management. This article highlights some of these findings.

A description of articles about AI systems that have the world wide web as their domain.