Retrieval system models: what’s new?

Automated retrieval systems In the postwar development of computing, most people thought of computers as machines for numerical applications. But some saw the potential for automatic text processing tasks, notably translation and document indexing and searching, even though words seemed much messier as data than numbers. For Roger, as one of these early researchers, building systems for language processing was both intellectually challenging and practically useful, and in the late 1950s he began to work on document retrieval (Needham 1963). The specialised scientific literature was growing too fast for the existing broadly-based and rigid indexing and classification schemes. This lack of appropriate retrieval tools, and the opportunities offered by computers, stimulated a critical examination of existing approaches to indexing and searching and the introduction of radically new ones. Document (or text) retrieval systems, like libraries before them, depend on a model of the way documents should be characterised to facilitate searching, and of effective strategies for searching. Many models for retrieval systems have been proposed since the 1950s. The most innovative, attractive, and successful have been those that, unlike the earlier library models