Author_Institution :
Univ. of Southern California, Los Angeles, CA, USA
Abstract :
Virtually cost-free publication on the World Wide Web has led to information overload. Artificial intelligence (AI), with its roots in knowledge representation, is experiencing a renaissance as new tools emerge to make the Web more tractable. Why do these Internet-based applications herald an AI renaissance? AI has come to play a crucial role in Information Age retrieval strategies. Internet-based applications can exploit a wide range of AI developments. In this survey, we look at examples of the following AI technologies: natural language processing (concept-based Internet searching); machine-learning (WebWatcher); heuristic rules for establishing preference (Letizia); rule-based/heuristic natural language processing (ContactFinder, FAQFinder, Globenet); and neural networks (Autonomy). This isn´t AI for AI´s sake-this renaissance is not one of stand-alone AI applications. Unlike first-generation AI applications, AI can now be embedded in heterogeneous networked computing environments and used for searching, retrieval and analysis of previously unimaginable quantities of data. Because the wealth of data makes direct human analysis impossible, AI-based support has become necessary to help users fully exploit that information. Our increasingly competitive and technology-driven world has reduced the time available to us for decision-making. To survive in this environment, we are increasingly turning to advanced computer technologies, such as intelligent agents, and delegating some of that decision-making to these electronic surrogates
Keywords :
Internet; artificial intelligence; electronic publishing; information retrieval systems; internetworking; natural languages; neural nets; software agents; AI renaissance; Autonomy; ContactFinder; FAQFinder; Globenet; Internet-based applications; Letizia; WebWatcher; World Wide Web; artificial intelligence; concept-based Internet searching; cost-free publication; decision-making; heterogeneous networked computing environments; heuristic processing; heuristic rules; information overload; intelligent agents; intranets; knowledge representation; machine-learning; natural language processing; neural networks; preference; retrieval strategies; rule-based processing; survey; Artificial intelligence; Computer networks; Decision making; IP networks; Information retrieval; Internet; Knowledge representation; Natural language processing; Neural networks; Web sites;