Guest Editors' Introduction to the Special Issue on Automated Text Categorization
Information Retrieval (IR), broadly intended as the discipline concerned with computerized access to data with poorly understood semantics, has grown in the last decade from a relatively small academic specialty to a richly articulated field at the forefront of computer science. The most conspicuous trend of the '90s within IR, aside from the emergence of Web search engines, has been the proliferation of a number of subtasks that depart from the mainstream " text search " paradigm, and tackle information access and use from a larger perspective. Tasks such as automated text categorization, information filtering (or routing), information extraction , text mining, question answering, text summarization, and topic (or event) detection and tracking, are no longer the " next frontier " of IR, but have become its pulsating heart. Central to the development of these novel (or relatively novel) IR tasks is the application of techniques from machine learning (ML). The key idea is that there is a lot of knowledge out there that can be brought to bear on information access tasks, but this knowledge hardly ever comes in the form of a systematized knowledge base, since such knowledge bases have to be manually built, and for most applications are thus unavailable or too costly to develop. Rather, knowledge manifests itself in the data, and has to be extracted from it; the shift of focus is thus from an " intensional " to an " extensional " notion of semantics, whereby the semantics of a concept is no more a declarative description of it or a set of rules for recognizing its instances, but is the set of contexts (e.g. documents) in which it is instantiated. In this setting, the goal of ML techniques is to help structure data in various respects. Probably the best known among the disciplines that lie at the crossroads of IR and ML is Automated Text Categorization (ATC), the task of building software tools capable of classifying text documents under one or more of a set of predefined categories or subject codes. ATC dates back to the early '60s, when it was mainly viewed as a means to alleviate the task of indexing scientific literature by controlled vocabulary terms. However, it was only in the early '90s that ATC fully flourished, under the pressure caused by the increased availability of ever larger numbers of text documents in digital form and by the ensuing need …