Presents a general mathematical framework for information retrieval, in which query evaluation is seen as a mapping from the free term algebra built by query descriptors and weights to the semantic algebra of evaluation value. Competing mathematical models that try to describe how retrieval systems behave are reviewed. (Author/MBR)

Examines through a series of mathematical models (theorems, descriptions, and examples), properties and operations on inverted files, which are used in an information retrieval system based on thesaurus with weighted descriptors. (CWM)

Analyzes the use of weights to denote a query representation and/or the indexing of a document as a generalization of a Boolean retrieval system. Criteria are given for the functions used to evaluate the relevance of the records to a specific query and a new evaluation approach is suggested. (CWM)

Presents a new method of document retrieval based on the fundamental operations of fuzzy set theory. Basic notions are introduced. Then the syntax and semantics of the proposed language for document retrieval is given, and an algorithm allocating documents to particular queries is described and its properties are discussed. (Author/CWM)

Proposes approach to integrating Boolean and statistical systems where Boolean queries are interpreted as a means of specifying term dependencies in relevant set of documents. Highlights include series of retrieval experiments designed to test retrieval strategy based on term dependence model and relation of results to other work. (18 references)…

Discusses methods of weighting of descriptors in document search patterns together with the concept of relative indexing and conditions which should be satisfied by descriptor weight. A procedure for modifiying document search patterns based on users' informational needs and opinions is outlined, and examples are given. Sixteen references are…

The problem of structuring sequences of instructional stimuli such that learning is optimized is modelled as a sequential decision problem with an imbedded mathematical model of learning providing a criterion function. Three types of optimization methods for such a representation are investigated for the specific case of paired-associate learning…