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In this article we present an algorithm which automatically extracts geopositional coordinate index terms from text to support georeferenced document indexing and retrieval. Under this algorithm, words and phrases containing geographic place names or characteristics are extracted from a text document and used as input to database functions which use spatial reasoning to approximate statistically the geoposition being referenced in the text. We conclude with a discussion of preliminary results and future work. © 1994 John Wiley & Sons, Inc.

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In this article, we describe and test a two‐stage algorithm based on a lexical collocation technique which maps from the lexical clues contained in a document representation into a controlled vocabulary list of subject headings. Using a collection of 4,626 INSPEC documents, we create a “dictionary” of associations between the lexical items contained in the titles, authors, and abstracts, and controlled vocabulary subject headings assigned to those records by human indexers using a likelihood ratio statistic as the measure of association. In the deployment stage, we use the dictionary to predict which of the controlled vocabulary subject headings best describe new documents when they are presented to the system. Our evaluation of this algorithm, in which we compare the automatically assigned subject headings to the subject headings assigned to the test documents by human catalogers, shows that we can obtain results comparable to, and consistent with, human cataloging. In effect, we have cast this as a classic partial match information retrieval problem. We consider the problem to be one of “retrieving” (or assigning) the most probably “relevant” (or correct) controlled vocabulary subject headings to a document based on the clues contained in that document. © 1998 John Wiley & Sons, Inc.

This article examines the structure and components of information storage and retrieval systems and information filtering systems. Analysis of the tasks performed in such selection systems leads to the identification of 13 components. Eight are necessarily present in all such systems, mechanized or not; the others may, but need not be, present. The authors argue that all selection systems can be represented in terms of combinations of these components. The components are of only two types: representations of data objects and functions that operate on them. Further, the functional components, or rules, reduce to two basic types: 1) transformation, making or modifying the members of a set of representations, and 2) sorting or partitioning. The representational transformations may be in the form of copies, excerpts, descriptions, abstractions, or mere identifying references. By partitioning, we mean dividing a set of objects by using matching, sorting, ranking, selecting, and other logically equivalent operations. The typical multiplicity of knowledge sources and of system vocabularies is noted. Some of the implications for the study, use, and design of information storage and retrieval systems are discussed.