The model assumes that the relevance assigned to a document by a juror is a random variable. (PF)

A threshold rule is analyzed and compared to the Neyman-Pearson procedure, indicating that the threshold rule provides a necessary but not sufficient measure of the minimal performance of a retrieval system, whereas Neyman-Pearson yields a better apriori decision for retrieval. (Author/MBR)

The use of a structured system of storing information, particularly relational indexing, can lead to situations in which items would not be retrieved due to technicalities of the system. To overcome such problems a study was made of condensations with the aim of providing a series of rules to apply. (4 references) (Author/SJ)

There are six major studies of the effect of indexing depth on retrieval performance. They differ in purpose, methodology, measures, indexing language, field of study, and data base--nevertheless, all have found depth of indexing to have the same effect upon information retrieval. (13 references) (Author/NH)

The work described was designed to test the feasibility of using automatic or semi-automatic methods to replace or reduce the intellectual effort involved in retrieving information from machine readable stores, particularly those using natural language. (Author)

Introduces the concept of relevance as viewed and applied in the context of IR (information retrieval) evaluation by presenting an overview of the multidimensionality and dynamic nature of the concept. Topics include classes and types of relevance; relevance criteria; degrees of relevance; levels of relevance; situational relevance; and…

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 results of a study that investigated the effect of variations in indexing exhaustivity on retrieval performance in a vector space retrieval system. The test collection of documents in the National Library of Medicine's Medline file indexed under cystic fibrosis is described, and use of the SMART information retrieval system is discussed.…

Discussion of information-retrieval effectiveness focuses on the use of multiple query or document representations, or multiple retrieval techniques, and combining the retrieval results (also known as data fusion). Experimental results with the SMART System (developed at Harvard and Cornell Universities for over 38 years) indicate combining…

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)

Reports on the progress of the natural language information retrieval project, a joint effort led by GE (General Electric) Research, and its evaluation at the sixth TREC (Text Retrieval Conference). Discusses stream-based information retrieval, which uses alternative methods of document indexing; advanced linguistic streams; weighting; and query…