Investigates the feasibility of using a distance measure for automatic sequential document classification. This property of the distance measure is used to design a sequential classification algorithm which classifies key words and analyzes them separately in order to assign primary and secondary classes to a document. (VT)

Presents a theoretical rationale for employing a form of information retrieval algorithm that helps searchers better navigate through large document collections by continually revising probability estimates for document subsets. The algorithm avoids assumptions of index term independence and predicts relevance more accurately with increasing…

Describes the advantages of a prototype retrieval system that uses statistically based ranked retrieval of records rather than traditional boolean methods, especially for end users. Several new techniques are also discussed including bit mapping, pruning, methods of building inverted files, and types of search engine. (26 references) (EAM)

Presents an approach to automatic matching and linkage of citations between databases which applied 14 coding techniques and measured their effectiveness in terms of efficiency of retrieval of duplicates with minimal false hits, reliability, and performance. (EAM)

Discusses the effect of including relevance data on the calculation of term discrimination values in bibliographic databases. Algorithms that calculate the ability of index terms to discriminate between relevant and non-relevant documents are described and tested. The results are discussed in terms of the relationship between term frequency and…

Discusses the feasibility of building intelligent rule- or weight-based algorithms into general-purpose software for interactive thesaurus navigation. Previous research is surveyed; practical investigations in thesaurus navigation and query enhancement are described; and implications for automatic or intelligent thesaurus navigation are…

Describes and discusses the findings of an experiment that tested the precision of full-text retrieval enhanced by 29 document term weighting algorithms at the lowest, middle, and highest levels of recall, and compared with the precision of full-text retrieval without algorithms and with paragraph retrieval. (29 references) (Author/CLB)

Discussion of the use of Latent Semantic Indexing to determine relevancy in information retrieval focuses on statistical regression and Bayesian methods. Topics include keyword searching; a multiple regression model; how the regression model can aid search methods; and limitations of this approach, including complexity, linearity, and…

Three specific contributions to the field of information retrieval are presented. The first two describe the establishment of an adaptive, interactive man-machine dialogue that produces a form of unsolicited librarian-like assistance for the user in his selection of index terms to characterize an indexing function. The data set upon which the…

The six papers that comprise this document deal with topics related to the National Institute for Occupational Safety and Health (NIOSH) and/or its online document retrieval system, NIOSHTIC. Specific subjects include: (1) a method to catalog multiple sources of NIOSH publications for dissemination; (2) an input rejection algorithm used to provide…

Describes experiments in Arabic information retrieval using 29 queries against a base of 355 bibliographic records. Using roots and stems as index terms worked better than words, and the root performed as well as or better than the stem at low recall levels and definitely better at high recall levels. (Contains 30 references.) (KRN)