Although a large part of a document retrieval system's resources are devoted to indexing, the question of how people do subject indexing has been the subject of much conjecture and only a little experimentation. This dissertation examines the relationships between a document being indexed and the index terms assigned to that document in an attempt…

These two indexing systems are briefly described and experimental evidence is cited showing that a combination of both theories produces better retrieval performance than either one alone. Appropriate conclusions are reached concerning viable automatic indexing procedures usable in practice. (Author)

Discusses the need to retrieve ideas in addition to content retrieval by such means as classification, subject headings, and keywords. Three models for idea retrieval are described, and a new model is proposed which combines selection, a controlled vocabulary, and logical structure. (seven references) (CLB)

Demonstrates the use of a directed graph model as a tool for finding desirable minimum vocabularies to be used in indexing and information retrieval. The basic algorithm is outlined, possible enhancements to the model are discussed, and further research questions are suggested. (Author/CLB)

Proposes split model for index term distribution in document set that uses rank function for high frequency terms and size function for low frequency terms; the point of transition is determined either empirically or by rule. Distributions to describe index term exhaustivity and term co-occurrence are considered briefly. (36 references) (EJS)

Discusses access to nontextual documents in large multimedia document bases. A hybrid information retrieval model, using queries in a hypertext environment for location of browsing areas, is presented; and two experiments using cluster-based descriptions of content are reported. (23 references) (EA)

Discusses and examines two approaches to concept-based retrieval of hypermedia information that improve a user's ability to navigate large systems--term indexing with semantically coupled thesauri and semantic hyperindexing. Visualization of index structures is discussed, and an example, the Cube of Contents retrieval model for the "Active…

Proposes an information retrieval system based on a hybrid model consisting of an inductive learning and neural network system. Evaluates the system's responses to incomplete queries and inconsistent indexing. Query terms, discriminant descriptors, and the American Documentation Institute's query and document titles used in the evaluation are…

Reports on two experiments investigating the relationship between topical subject expertise and the assessment of relevance. Results indicate that topical subject expertise enhances effects of the semantic distance model (SDM), and that relevance assessment is a contingent, psychological phenomenon that is part of the human-perception task of…

Examines some nonbook materials with respect to an aboutness model of indexing, showing that there are instances that defy subject indexing. These occur not so much because of the nature of the medium but because it is being used for nondocumentary purposes or because the subject referenced is nonlexical. (Contains 20 references.) (KRN)

Presents a set-oriented view of information retrieval and defines a precise model to capture this approach. A number of consequences of the model, such as the limitations implied by a finite index vocabulary, are examined, and the various ways in which the set orientation can influence thinking about information retrieval is discussed. (14…

Relative effectiveness of indexing using full-text or less than full-text was tested using non-Boolean, chaining type of file structure and searching method. Indexing was done using titles, abstracts, full-text, references, and various combinations; Goffman's indirect method of information retrieval was used to structure and search file.…

Proposes a model that assists in understanding indexing on the World Wide Web and presents an experiment assessing the validity of Inverse Document Frequency (IDF) as a term weighting strategy for Web documents. Findings indicate that IDF scores are not stable in the heterogeneous and dynamic context of the Web. (Author/AEF)

Describes the Belief Function Model for automatic indexing and ranking of documents which is based on a controlled vocabulary and on term frequencies in each document. Belief Function Theory is explained, and the Belief Function Model is compared to the Standard Vector Space Model. (17 references) (LRW)

The first of three articles describes fluctuations in subject searching on online catalogs over time; the second describes the level of agreement between a research library's use of subject headings and the Library of Congress subject headings; and the third discusses the advantages of incorporating Library of Congress subject headings into online…