Describes a modified frequency-sensitive self-organization (FSO) algorithm for image data compression and the associated VLSI architecture. Topics discussed include vector quantization; VLSI neural processor architecture; detailed circuit implementation; and a neural network vector quantization prototype chip. Examples of images using the FSO…

Analyzes the amount of compression possible when arithmetic coding is used for text compression in conjunction with various input models. Algorithms are analyzed; modeling effects are considered; scaling is discussed; higher order models are examined, including prediction by partial matching; and coding effects are described. (34 references) (LRW)

Identifies four components of a good predictive lossless image compression method: (1) pixel sequence, (2) image modeling and prediction, (3) error modeling, and (4) error coding. Highlights include Laplace distribution and a comparison of the multilevel progressive method for image coding with the prediction by partial precision matching method.…

Presents new methods for compressing bit matrices in large information retrieval systems which exploit possible correlations between rows of words and columns of documents. Three encoding methods are tested and compared--Shannon-Fano, arithmetic, and Huffman--and an appendix discusses binomial coefficients. (20 references) (LRW)

Discusses end-user searching in Boolean information retrieval systems considers the role of search intermediaries and proposes a model of user preferences that incorporates a user's profile. Highlights include document representation; information queries; document output ranking; calculating user profiles; and selecting documents for a local…

Discusses the problems of compressing a large textual database for storage on CD-ROM. A text-compression algorithm is presented, new algorithms for compression of indices are described, and the ARTFL (American and French Research on the Treasury of the French Language) database is used as an example. (14 references) (LRW)

Illustrates that the Poisson-lognormal model provides good fits to a diverse set of distributions commonly studied in bibliometrics and scientometrics. Topics discussed include applications to the empirical data sets related to the laws of Lotka, Bradford, and Zipf; causal processes that could generate lognormal distributions; and implications for…

Proposes a new learning algorithm to improve the retrieval effectiveness of the search system used in the hypertext environment using an extended Boolean model with links to improve the ranking of retrieved items. Highlights include the basic retrieval scheme, the learning scheme, and a review of basic probabilistic retrieval models. (Contains 32…