Discussion of probabilistic information retrieval (IR) systems challenges the probability ranking principle in IR from the perspective of (1) signal detection-decision theory and (2) utility theory. Calibration, certainty, and independent assessment are discussed in terms of the relevance of documents, and standard retrieval policies are analyzed.…

Describes SENTINEL, a prototype information-retrieval system that is a fusion of multiple information-retrieval technologies, integrating n-grams, a vector space model, and a neural network training rule. Discusses three-dimensional visualization capability, precision and recall, mathematical representation of a document, query building, and…

Presents an approach to a Genetic Information Retrieval Agent Filter (GIRAF) that filters and ranks documents retrieved from the Internet according to users' preferences by using a Genetic Algorithm and fuzzy set theory to handle the imprecision of users' preferences and users' evaluation of the retrieved documents. (Author/LRW)

Reports the results of a study of users' perceptions of relevance of documents that focused on evaluating the effectiveness of a telephone-based information retrieval service. Studies how users' perceptions varied depending on the form in which retrieved documents were presented, from full text to a machine-spoken summary. (Contains 27…

Presents a unified mathematical definition for the classical models of information retrieval and identifies a mathematical structure behind relevance feedback. Highlights include vector information retrieval; probabilistic information retrieval; and similarity information retrieval. (Contains 118 references.) (Author/LRW)

Presents notations and definitions necessary to identify the concepts and relationships that are important in modelling information retrieval objects and processes in the context of vector spaces. Earlier work on the use of vector models is evaluated in terms of the concepts introduced and certain problems are identified. (Author/EM)

Describes a study that used the TREC information-retrieval test collection to evaluate Visual Information Retrieval Interfaces (VIRIs). Discusses multiple-similarity measures, scaling properties, and MLE (maximum likely method), and suggests that cosine-vector and overlap measures for similarity appear to recover optimal data relationships among…

Briefly surveys the numerous applications of fuzzy set theory on data representation and information retrieval. The importance of fuzzy set theory with respect to information systems is illustrated with a bibliography of 86 papers that describe data systems that are somehow "fuzzy." (Author/EM)

Isolates a number of criteria that should be met by any Boolean system generalized to have a weighting capability, and proves that the one weighting rule satisfying these conditions satisfies most of the other properties associated with Boolean algebra as well. Thirteen references are listed. (FM)

Replies to Stephen E. Robinson's article on the role of fuzzy set theory in information science (Journal of the American Society for Information Science; v29 n6 Nov 1978), particularly with regard to Robinson's discussions of uncertainty, min/max connectives, and relevance. (FM)

Responds to Barbara A. Cerny's reaction to Robinson's article on the role of fuzzy set theory in information science, addressing Cerny's points about probability theory and statistical uncertainty. (FM)

This study examined the effect of order of presentation of document citations on users' relevance judgments. Results indicated that users are not influenced by order of presentation when fewer than 15 citations are presented. (four references) (MES)

Describes a modular system called the TemplateFiller System that digests large volumes of text, filtering out irrelevant articles and distilling the remainder into templates that represent information from the articles in pairs. Other research in template filling is reviewed, and precision and recall using the TemplateFiller is evaluated.…

Discussion of information-retrieval test collections focuses on a study of TREC documents that used scaling and visualization of documents using a maximum-likelihood estimation method to examine the relevance of documents retrieved. Discusses clustering, similarity measures, isomorphism, and semantic relevance. (LRW)

The derivation of a general retrieval effectiveness measure is investigated. Inconsistencies in the definition of relative importance are resolved, and it is shown that the influence of the assigned weight on the effectiveness measure can produce counterintuitive results. An alternative effectiveness measure provided by the Marczewski-Steinhaus…