Abstract: For column compression of tabular data, similar type data segments are classified into classes for grouping the data segments into compression streams associated with each one of the classes. The compression streams are encoded based on a class-specific optimized encoding operation. The compression streams into one output buffer, wherein the compression streams are extracted.

Abstract: For multiplexer classification for column compression of tabular data, similar type data segments are classified into classes for grouping the data segments into compression streams associated with each one of the classes. The compression streams are encoded based on a class-specific optimized encoding operation. The compression streams into one output buffer, wherein the compression streams are extracted.

Abstract: Exemplary method, system, and computer program product embodiments for real-time selection of compression operations are provided. In one embodiment, by way of example only, available compression operations are initialized according to an assigned success factor. The available compression operations are tested for determining if at least one of the compression operations yields a compression ratio greater than a minimal compression ratio. The available compression operations selected in real time for compressing at least one of the data blocks is applied. Additional system and computer program product embodiments are disclosed and provide related advantages.

Abstract: Exemplary method, system, and computer program product embodiments for real-time image recompression are provided. In one embodiment, by way of example only, compressed segments that are identified as having used at least one of a plurality of inefficient compression operations are partially decoded. The compressed segments are recompressed by employing context mapping. Additional system and computer program product embodiments are disclosed and provide related advantages.

Abstract: Exemplary methods, computer systems, and computer program products for processing a previously compressed data stream in a computer environment are provided. In one embodiment, the computer environment is configured for separating a previously compressed data stream into an input data block including a header input block having a previously compressed header. Sequences of bits are included with the input data block. Compression scheme information is derived from the previously compressed header. The input data block is accessed and recompressed following the header input block in the previously compressed data stream one at a time using block-image synchronization information. Access to the block-image synchronization information is initialized by the compression scheme information to generate an output data block. The block-image synchronization information is used to provide decompression information to facilitate decompression of the results of the output data block.

Abstract: Exemplary methods, computer systems, and computer program products for processing a previously compressed data stream in a computer environment are provided. In one embodiment, the computer environment is configured for separating a previously compressed data stream into an input data block including a header input block having a previously compressed header. Sequences of bits are included with the input data block. Compression scheme information is derived from the previously compressed header. The input data block is accessed and recompressed following the header input block in the previously compressed data stream one at a time using block-image synchronization information. Access to the block-image synchronization information is initialized by the compression scheme information to generate an output data block. The block-image synchronization information is used to provide decompression information to facilitate decompression of the results of the output data block.

Abstract: Exemplary methods, computer systems, and computer program products for processing a previously compressed data stream in a computer environment are provided. In one embodiment, the computer environment is configured for separating a previously compressed data stream into an input data block including a header input block having a previously compressed header. Sequences of bits are included with the input data block. Compression scheme information is derived from the previously compressed header. The input data block is accessed and recompressed following the header input block in the previously compressed data stream one at a time using block-image synchronization information. Access to the block-image synchronization information is initialized by the compression scheme information to generate an output data block. The block-image synchronization information is used to provide decompression information to facilitate decompression of the results of the output data block.

Abstract: The present invention is a system and method for lossless compression of data. The invention consists of a neural network data compression comprised of N levels of neural network using a weighted average of N pattern-level predictors. This new concept uses context mixing algorithms combined with network learning algorithm models. The invention replaces the PPM predictor, which matches the context of the last few characters to previous occurrences in the input, with an N-layer neural network trained by back propagation to assign pattern probabilities when given the context as input. The N-layer network described below, learns and predicts in a single pass, and compresses a similar quantity of patterns according to their adaptive context models generated in real-time. The context flexibility of the present invention ensures that the described system and method is suited for compressing any type of data, including inputs of combinations of different data types.