Abstract: Described are a system, method, and computer program product for generating a synthetic control group. The method includes receiving transaction data associated a first set of transaction accounts in a first time period and generating a synthetic control group including a subset of transaction accounts. The method also includes determining, for each transaction account of the synthetic control group, a propensity score representative of a likelihood of said transaction account being associated with a test group, and a predictive spending score for a second time period. The method further includes balancing the synthetic control group and altering at least one operational parameter of a computer-implemented advertisement program to be executed in a second time period based on the transaction data and the synthetic control group. The method further includes executing the computer-implemented advertisement program in the second time period based on the at least one operational parameter that was altered.

Abstract: Described are a system, method, and computer program product for generating a data storage server distribution pattern. The method includes determining a set of servers and raw data to be stored. The method also includes transforming the raw data according to an error-correcting code scheme to produce distributable data. The method further includes determining a server reliability of each server in the set of servers. The method further includes generating the data storage server distribution pattern based on maximizing a system reliability relative to maximizing a system entropy. System reliability may be based on a minimum reliability of the set of servers, and system entropy may be based on a cumulated information entropy of each server of the set of servers. The method further includes distributing the distributable data to be stored across at least two servers of the set of servers according to the data storage server distribution pattern.

Abstract: Described are a system, method, and computer program product for generating a synthetic control group. The method includes receiving transaction account data and transaction data associated with transactions completed by a first set of transaction accounts with a target merchant. The method also includes generating a synthetic control group including a subset of transaction accounts sampled from the first set of transaction accounts. The method further includes determining, for each transaction account of the synthetic control group, a propensity score. The method further includes assigning an entropy balancing weight to each transaction account of the synthetic control group. The method further includes altering, based on the synthetic control group, at least one operational parameter of a computer-implemented advertisement program to be executed.

Abstract: Systems, methods, and computer program products are provided for load balancing for processing large data sets. The method includes identifying a number of segments and a transaction data set comprising transaction data for a plurality of transactions, the transaction data for each transaction of the plurality of transactions comprising a transaction value, determining an entropy of the transaction data set based on the transaction value of each transaction of the plurality of transactions, segmenting the transaction data set into the number of segments based on the entropy of the transaction data set and balancing respective entropies of each segment of the number of segments, and distributing processing tasks associated with each segment of the number of segments to at least one processor of a plurality of processors to process each transaction in each respective segment.

Abstract: Systems, methods, and computer program products are provided for load balancing for processing large data sets. The method includes identifying a number of segments and a transaction data set comprising transaction data for a plurality of transactions, the transaction data for each transaction of the plurality of transactions comprising a transaction value, determining an entropy of the transaction data set based on the transaction value of each transaction of the plurality of transactions, segmenting the transaction data set into the number of segments based on the entropy of the transaction data set and balancing respective entropies of each segment of the number of segments, and distributing processing tasks associated with each segment of the number of segments to at least one processor of a plurality of processors to process each transaction in each respective segment.

Abstract: Described are a system, method, and computer program product for generating a data storage server distribution pattern. The method includes determining a set of servers and raw data to be stored. The method also includes transforming the raw data according to an error-correcting code scheme to produce distributable data. The method further includes determining a server reliability of each server in the set of servers. The method further includes generating the data storage server distribution pattern based on maximizing a system reliability relative to maximizing a system entropy. System reliability may be based on a minimum reliability of the set of servers, and system entropy may be based on a cumulated information entropy of each server of the set of servers. The method further includes distributing the distributable data to be stored across at least two servers of the set of servers according to the data storage server distribution pattern.

Abstract: Described are a system, method, and computer program product for generating a data storage server distribution pattern. The method includes determining a set of servers and raw data to be stored. The method also includes transforming the raw data according to an error-correcting code scheme to produce distributable data. The method further includes determining a server reliability of each server in the set of servers. The method further includes generating the data storage server distribution pattern based on maximizing a system reliability relative to maximizing a system entropy. System reliability may be based on a minimum reliability of the set of servers, and system entropy may be based on a cumulated information entropy of each server of the set of servers. The method further includes distributing the distributable data to be stored across at least two servers of the set of servers according to the data storage server distribution pattern.

Abstract: Systems, methods, and computer program products are provided for load balancing for processing large data sets. The method includes identifying a number of segments and a transaction data set comprising transaction data for a plurality of transactions, the transaction data for each transaction of the plurality of transactions comprising a transaction value, determining an entropy of the transaction data set based on the transaction value of each transaction of the plurality of transactions, segmenting the transaction data set into the number of segments based on the entropy of the transaction data set and balancing respective entropies of each segment of the number of segments, and distributing processing tasks associated with each segment of the number of segments to at least one processor of a plurality of processors to process each transaction in each respective segment.

Abstract: Described are a system, method, and computer program product for generating a synthetic control group. The method includes receiving transaction account data and transaction data associated with transactions completed by a first set of transaction accounts with a target merchant. The method also includes generating a synthetic control group including a subset of transaction accounts sampled from the first set of transaction accounts. The method further includes determining, for each transaction account of the synthetic control group, a propensity score. The method further includes assigning an entropy balancing weight to each transaction account of the synthetic control group. The method further includes altering, based on the synthetic control group, at least one operational parameter of a computer-implemented advertisement program to be executed.

Abstract: Described are a system, method, and computer program product for generating a synthetic control group. The method includes receiving transaction account data and transaction data associated with transactions completed by a first set of transaction accounts with a target merchant. The method also includes generating a synthetic control group including a subset of transaction accounts sampled from the first set of transaction accounts. The method further includes determining, for each transaction account of the synthetic control group, a propensity score. The method further includes assigning an entropy balancing weight to each transaction account of the synthetic control group. The method further includes altering, based on the synthetic control group, at least one operational parameter of a computer-implemented advertisement program to be executed.

Abstract: Described are a system, method, and computer program product for generating a synthetic control group. The method includes receiving transaction account data and transaction data associated with transactions completed by a first set of transaction accounts with a target merchant. The method also includes generating a synthetic control group including a subset of transaction accounts sampled from the first set of transaction accounts. The method further includes determining, for each transaction account of the synthetic control group, a propensity score. The method further includes assigning an entropy balancing weight to each transaction account of the synthetic control group. The method further includes altering, based on the synthetic control group, at least one operational parameter of a computer-implemented advertisement program to be executed.

Abstract: Systems, methods, and computer program products are provided for load balancing for processing large data sets. The method includes identifying a number of segments and a transaction data set comprising transaction data for a plurality of transactions, the transaction data for each transaction of the plurality of transactions comprising a transaction value, determining an entropy of the transaction data set based on the transaction value of each transaction of the plurality of transactions, segmenting the transaction data set into the number of segments based on the entropy of the transaction data set and balancing respective entropies of each segment of the number of segments, and distributing processing tasks associated with each segment of the number of segments to at least one processor of a plurality of processors to process each transaction in each respective segment.

Abstract: Systems, methods, and computer program products are provided for load balancing for processing large data sets. The method includes identifying a number of segments and a transaction data set comprising transaction data for a plurality of transactions, the transaction data for each transaction of the plurality of transactions comprising a transaction value, determining an entropy of the transaction data set based on the transaction value of each transaction of the plurality of transactions, segmenting the transaction data set into the number of segments based on the entropy of the transaction data set and balancing respective entropies of each segment of the number of segments, and distributing processing tasks associated with each segment of the number of segments to at least one processor of a plurality of processors to process each transaction in each respective segment.

Abstract: Described are a system, method, and computer program product for generating a data storage server distribution pattern. The method includes determining a set of servers and raw data to be stored. The method also includes transforming the raw data according to an error-correcting code scheme to produce distributable data. The method further includes determining a server reliability of each server in the set of servers. The method further includes generating the data storage server distribution pattern based on maximizing a system reliability relative to maximizing a system entropy. System reliability may be based on a minimum reliability of the set of servers, and system entropy may be based on a cumulated information entropy of each server of the set of servers. The method further includes distributing the distributable data to be stored across at least two servers of the set of servers according to the data storage server distribution pattern.

Abstract: Systems, methods, and computer program products are provided for load balancing for processing large data sets. The method includes identifying a number of segments and a transaction data set comprising transaction data for a plurality of transactions, the transaction data for each transaction of the plurality of transactions comprising a transaction value, determining an entropy of the transaction data set based on the transaction value of each transaction of the plurality of transactions, segmenting the transaction data set into the number of segments based on the entropy of the transaction data set and balancing respective entropies of each segment of the number of segments, and distributing processing tasks associated with each segment of the number of segments to at least one processor of a plurality of processors to process each transaction in each respective segment.

Abstract: The present invention is a system, method, and computer program product for compression and reconstruction of a color image using principal components transformation. The method is performed on a computer or other programmable data processing apparatus. The method is performed in combination with the standard JPEG image compression technique. According to the invention, the method receives color image information. The received color image information is converted into intrinsic color information. The intrinsic color information is based on the color image's intrinsic and unique color distribution.

Abstract: The present invention is a system, method, and computer program product for compression and reconstruction of a color image using principal components transformation. The method is performed on a computer or other programmable data processing apparatus. The method is performed in combination with the standard JPEG image compression technique. According to the invention, the method receives color image information. The received color image information is converted into intrinsic color information. The intrinsic color information is based on the color image's intrinsic and unique color distribution.