hours in the day anymore, are there? Everybody seems to have a stack of things waiting that just had to be done yesterday, and the problem only gets worse, not better. Information overload: it's the bane of our times. This impression seems so realistic that any help in handling at least some simple tasks is usually appreciated. The Internet's recent ascendancy-not only in the research community but also in many areas of everyday life-is a major culprit. No longer confined to providing researchers access to data, the Internet is often the source of choice for information about everything from what's happening around the world, to where to get the best airline tickets, to how to cook a particular dish, to where to find the best hiking trails. It's wonderful, but it also causes headaches. The impact on computer systems is particularly pronounced. When different people come together without centralized rules and guidance, many creative and pleasant, as well as some less pleasant, aspects emerge. So, when putting information on the World Wide Web, each of us can decide what to put there and how to organize it. The result is a distributed, world-wide-accessible information source that contains nonhomogeneous data organized according to different human association models and value schemes. While this personal touch and opportunity for creativity can be extremely useful for humans when providing and obtaining information, most computer systems have a hard time coping with the complexity, especially because people want information sooner rather than later. The large amounts of information available in electronic form on the Web challenges the research community with its distributed organization; its arbitrary mixture of text, speech, image, and video in the same document; and the dynamic nature of the provided information. A number of systems have emerged for helping users browse the Web, some based on content analysis using mostly text from Web documents, and others relying on other information about document relevancy, such as user ratings. Recent developments at the intersection of information retrieval and machine learningas well as work in intelligent agents and intelligent user interfaces-offer novel solutions for helping users quickly select the information they want. A wide range of researchers are involved in the intensive development of methods for using machine-learning techniques on text databases, called text learning, which combine research in machine learning with information retrieval. This article surveys a part of text learning where supervised learning methods are used for text
A wide range of researchers are involved in the intensive development of methods for using machine learning techniques on text databases, which are called text learning and combine research in machine learning with information retrieval REF .
Text-learning and related intelligent agents: a survey
IEEE Intelligent Systems & Their Applications
Computer Science