Abstract: A method for projection mining comprises performing a first projection on a first data object of a first type comprising a plurality of data entries and a second data object of a second type comprising a plurality of data entries to create definitions of attributes of the first data object and definitions of attributes of the second data object, performing a second projection of the definitions of the attributes of the first data object and the definitions of the attributes of the second data object into a space of meta-attributes based on semantic relationships among the attributes of the first data object and the second data object, learning relationships between the space of meta-attributes formed by the projections of the first data object and the second data object and a space of meta-attributes relating to new data not included in the first data object and the second data object, and generating at least one new data object of the first or second type based on the new data using the learned relationships

Abstract: A method for projection mining comprises performing a first projection on a first data object of a first type comprising a plurality of data entries and a second data object of a second type comprising a plurality of data entries to create definitions of attributes of the first data object and definitions of attributes of the second data object, performing a second projection of the definitions of the attributes of the first data object and the definitions of the attributes of the second data object into a space of meta-attributes based on semantic relationships among the attributes of the first data object and the second data object, learning relationships between the space of meta-attributes formed by the projections of the first data object and the second data object and a space of meta-attributes relating to new data not included in the first data object and the second data object, and generating at least one new data object of the first or second type based on the new data using the learned relationships

Abstract: A method, system, and computer program product for allocating data mining processing tasks that does not use complex internal schemes, yet results in better performance than is possible with general-purpose operating system based schemes. The present invention uses a data mining agent that operates autonomously, proactively, reactively, deliberatively, and cooperatively to allocate and reallocate data mining processing tasks among computer systems, and/or among processors. The data mining agent reacts to its own environment, determines if a data mining activity can be completed as expected, solicits bids from other data mining agents, determines if another data mining system could complete the data mining activity and migrates that data mining activity to the selected data mining system.

Abstract: A method for projection mining comprises performing a first projection on a first data object of a first type comprising a plurality of data entries and a second data object of a second type comprising a plurality of data entries to create definitions of attributes of the first data object and definitions of attributes of the second data object, performing a second projection of the definitions of the attributes of the first data object and the definitions of the attributes of the second data object into a space of meta-attributes based on semantic relationships among the attributes of the first data object and the second data object, learning relationships between the space of meta-attributes formed by the projections of the first data object and the second data object and a space of meta-attributes relating to new data not included in the first data object and the second data object, and generating at least one new data object of the first or second type based on the new data using the learned relationships

Abstract: A method, system, and computer program product for allocating data mining processing tasks that does not use complex internal schemes, yet results in better performance than is possible with general-purpose operating system based schemes. The present invention uses a data mining agent that operates autonomously, proactively, reactively, deliberatively, and cooperatively to allocate and reallocate data mining processing tasks among computer systems, and/or among processors. The data mining agent reacts to its own environment, determines if a data mining activity can be completed as expected, solicits bids from other data mining agents, determines if another data mining system could complete the data mining activity and migrates that data mining activity to the selected data mining system.

Abstract: A method, system, and computer program product for allocating data mining processing tasks that does not use complex internal schemes, yet results in better performance than is possible with general-purpose operating system based schemes. The present invention uses a data mining agent that operates autonomously, proactively, reactively, deliberatively, and cooperatively to allocate and reallocate data mining processing tasks among computer systems, and/or among processors. The data mining agent reacts to its own environment, determines if a data mining activity can be completed as expected, solicits bids from other data mining agents, determines if anther data mining system could complete the data mining activity and migrates that data mining activity to the selected data mining system.

Abstract: A system for collecting and distributing information to and from a plurality of electronically controlled machines. The system is designed to collect information from robots, industrial machines, and other types of equipment that produce real-time information. The machines are coupled to a data collector module using a public domain communication protocol. The data collector module is coupled in data communication to a main server which has a mechanism for publishing the data received from the electronically controlled machines over a network to one or more clients. The main server also has an authenticator for verifying the identity of clients accessing the system through the network, and a communication module for streaming the data from the electronically controlled machines. Information and programming may also be transferred from the clients to the machines through the system to allow remote control of the machines.

Abstract: An application programming interface, computer program product implementing the application programming interface, and a system implementing the application programming interface, which provides an advanced interface including support for hierarchical and object-oriented programming languages and sophisticated programming language constructs, and does not need to be integrated using additional tools.