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Information Processing and… | 9 |
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Bookstein, Abraham | 1 |
Chen, Oscal T.-C. | 1 |
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Kraft, Donald H. | 1 |
Lin, Jianhua | 1 |
Markas, Tassos | 1 |
Mazur, Zygmunt | 1 |
Radecki, Tadeusz | 1 |
Reif, John | 1 |
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Markas, Tassos; Reif, John – Information Processing and Management, 1992
Presents a class of distortion controlled vector quantizers that are capable of compressing images so they comply with certain distortion requirements. Highlights include tree-structured vector quantizers; multiresolution vector quantization; error coding vector quantizer; error coding multiresolution algorithm; and Huffman coding of the quad-tree…
Descriptors: Algorithms, Coding, Information Processing, Mathematical Formulas

Lin, Jianhua; And Others – Information Processing and Management, 1992
Analyzes the computational complexity of optimal binary tree pruning for tree-structured vector quantization. Topics discussed include the combinatorial nature of the optimization problem; the complexity of optimal tree pruning; and finding a minimal size pruned tree. (11 references) (LRW)
Descriptors: Algorithms, Coding, Computation, Information Processing

Chen, Oscal T.-C.; And Others – Information Processing and Management, 1992
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…
Descriptors: Algorithms, Coding, Information Processing, Mathematical Formulas

Howard, Paul G.; Vitter, Jeffrey Scott – Information Processing and Management, 1992
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)
Descriptors: Algorithms, Coding, Computation, Information Processing

Kar, Gautam; White, Lee J. – Information Processing and Management, 1978
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)
Descriptors: Algorithms, Automatic Indexing, Classification, Information Processing

Bookstein, Abraham; And Others – Information Processing and Management, 1992
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)
Descriptors: Algorithms, Coding, Full Text Databases, Indexes

Mazur, Zygmunt – Information Processing and Management, 1979
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)
Descriptors: Algorithms, Indexes, Information Processing, Information Retrieval

Waller, W. G.; Kraft, Donald H. – Information Processing and Management, 1979
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)
Descriptors: Algorithms, Evaluation Criteria, Information Processing, Information Retrieval

Radecki, Tadeusz – Information Processing and Management, 1979
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)
Descriptors: Algorithms, Information Processing, Information Retrieval, Information Storage