Examines statistical techniques for exploiting relevance information to weight search terms. These techniques are presented as a natural extension of weighting methods using information about the distribution of index terms in documents in general. (Author)

Assesses the retrieval effectiveness of automatically constructed interdocument hypertext links in information retrieval (IR). Describes experiments using statistical and probabilistic techniques that were designed to obtain evidence concerning the usefulness of querying and browsing automatically constructed IR hypertexts. Results indicate a…

Introduces a new model of viewing documents based on citing-cited relationship between them. Using Bayes' decision theory, it is shown how source document may be indexed and weighted by relevant cited document features, corresponding to one pass relevance feedback Model 1 (probabilistic indexing) or Model 2 (probabilistic retrieval). (24…

Presents adaptation of a probabilistic theoretical model previously used in relevance feedback for use in automatic indexing of documents (in the sense of imitating) human indexers. Methods for model application are proposed, independence assumptions used in the model are interpreted, and the probability of a dependence model is discussed.…

ASSOCIATIVE ADJUSTMENTS TO A DOCUMENT FILE ARE CONSIDERED AS A MEANS FOR IMPROVING RETRIEVAL. A THEORETICAL INVESTIGATION OF THE STATISTICAL PROPERTIES OF A GENERALIZED MISMATCH MEASURE WAS CARRIED OUT AND IMPROVEMENTS IN RETRIEVAL RESULTING FROM PERFORMING ASSOCIATIVE REGRESSION ADJUSTMENTS ON DATA FILE WERE EXAMINED BOTH FROM THE THEORETICAL AND…

This report explains the following mathematical techniques which may be used for relating search requests to documents contained in a library: (1) Boolean Algebraic Retrieval, (2) Linear Statistical Retrieval, (3) Statistical Association Techniques for expanding a query and/or for expanding the set of retrieval documents, (4) Vector Space…

Presents results of simulations that were conducted to test the effects of errors in estimation of individual term probabilities on the performance of a probabilistic information retrieval (PIR) system. Assigning index terms to documents is described; an information retrieval system called Helpnet is explained; and relevance, ranking, and…

Describes the Belief Function Model for automatic indexing and ranking of documents which is based on a controlled vocabulary and on term frequencies in each document. Belief Function Theory is explained, and the Belief Function Model is compared to the Standard Vector Space Model. (17 references) (LRW)

Discusses information retrieval systems and the need to have them adapt to user needs, integrate information in any format, reveal patterns and trends in information, and answer questions. Topics include statistics and probability; natural language processing; intelligent agents; concept mapping; machine-aided indexing; text mining; filtering;…

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…

Examines the use of various statistical techniques for generating domain-oriented multiword vocabulary terms for natural language database systems. Conclusions show the vocabulary clustering effect should be considered when making significance calculations and that a simple ratio of subject matter relative frequency to total sample relative…

The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…