Describes a relevance decision model based on a threshold concept and techniques to validate the model which were developed through pretesting. (Author/PF)

Presents two partitioning methods for signature files and a method of fast weight computation to implement a document ranking strategy. Storage requirements, number of disk accesses, and processing time for these methods are compared with two other access methods. Merits of the partitioning methods are summarized. (20 references) (MES)

Describes an information system interface that allows specification of uncertain queries and combines evidence about the relevance of documents to produce an overall ranking. Results of an experiment that addressed some of the cognitive aspects of such an interface are also reported. (22 references) (Author/MES)

Discussion of the interpretation of user queries in information retrieval highlights theoretical models that utilize user characteristics maintained in the form of a user profile. Various query/profile interaction models are identified, and an experiment is described that tested the relevance of retrieved documents based on various models. (29…

Discussion of relevance and the needs of the users in information retrieval focuses on a deductive object-oriented approach and suggests eight inference rules for the deduction. Highlights include characteristics of a deductive object-oriented system, database and data modeling language, implementation, and user interface. (Contains 24…

Discusses expert systems and their value as components of information retrieval systems related to semantic inference, and describes IOTA, a model of an intelligent information retrieval system which emphasizes natural language query processing. Experimental results are discussed and current and future developments are highlighted. (Author/LRW)

Describes an expected precision (EP) measure designed to predict document retrieval performance. Highlights include decision theoretic models; precision and recall as measures of system performance; EP graphs; relevance feedback; and computing the retrieval status value of a document for two models, the Binary Independent Model and the Two Poisson…

Formulates a model to accommodate the hypothesis that, if the content representation items of documents in a database are neither totally independent nor highly correlated, combining them in a certain way may increase information retrieval effectiveness. The results of a small experiment that tested this hypothesis are presented. (Author/JD)

Describes rough sets theory and discusses the advantages it offers for information retrieval, including the implicit inclusion of Boolean logic, term weighting, ranked retrieval output, and relevance feedback. Rough set formalism is compared to Boolean, vector, and fuzzy models of information retrieval and a small scale evaluation of rough sets is…

Reports information retrieval experiments comparing the performance of a probabilistic retrieval model that incorporates interdocument links with the simpler spreading activation strategy. Results indicated that the overall improvement obtained by including hypertext links in the retrieval model was low. (30 references) (EA)

Describes the three subsystems of an information retrieval system (document descriptions, queries, and matching algorithms) and argues that the interdependency of these subsystems requires adaptation for the system to perform when any component changes. An algorithm for redescribing documents, in response to changes in queries and retrieval rules,…

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…

Discusses approaches to the integration of query-based information retrieval and browsing in a hypertext network. A prototype system developed to evaluate the proposed approach in terms of retrieval effectiveness and search efficiency is presented, and design and implementation issues concerning the prototype are considered. (30 references) (EA)

Discusses two models of selecting information sources--Cost/Benefit (information seekers select sources on basis of expected benefits and costs), and Least-Effort (seekers select sources on basis of minimizing effort or cost). Results of a study proposing that users place different weights on costs and benefits are presented. (EJS)

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)