Abstract: A generic categorization method may include receiving interaction data on a distributed computing system operating on a plurality of computing nodes. The distributed computing system may distribute the received interaction data across the plurality of nodes. On each node, categorization rules may be applied to the interaction data via parallel processing. The results, which may include a category associated with each interaction, may be written to a distributed storage system. A user interface may allow a user to define the categorization rules and schemas of interaction data.

Abstract: A generic categorization method may include receiving interaction data on a distributed computing system operating on a plurality of computing nodes. The distributed computing system may distribute the received interaction data across the plurality of nodes. On each node, categorization rules may be applied to the interaction data via parallel processing. The results, which may include a category associated with each interaction, may be written to a distributed storage system. A user interface may allow a user to define the categorization rules and schemas of interaction data.

Abstract: A system or method may receive, on a distributed computing system comprising a plurality of computing nodes, raw interaction data describing at least one interaction between two or more parties. The distributed computing may implement a map-reduce algorithm to map the raw interaction data into one or more entities, wherein each entity describes an attribute of an interaction. The distributed computing system my further update an interaction table to include each of the entities, wherein entities describing attributes of the same interaction are correlated.

Abstract: A system or method may receive, on a distributed computing system comprising a plurality of computing nodes, raw interaction data describing at least one interaction between two or more parties. The distributed computing may implement a map-reduce algorithm to map the raw interaction data into one or more entities, wherein each entity describes an attribute of an interaction. The distributed computing system my further update an interaction table to include each of the entities, wherein entities describing attributes of the same interaction are correlated.

Abstract: A generic categorization method may include receiving interaction data on a distributed computing system operating on a plurality of computing nodes. The distributed computing system may distribute the received interaction data across the plurality of nodes. On each node, categorization rules may be applied to the interaction data via parallel processing. The results, which may include a category associated with each interaction, may be written to a distributed storage system. A user interface may allow a user to define the categorization rules and schemas of interaction data.

Abstract: A method for reliably communicating unreliable protocol packets by encapsulating one or more unreliable protocol packets in a packet constructed according to a predefined format. The method further employs an acknowledgement mechanism whereby a receiver of packets acknowledges reception by responding with a packet containing information pertaining to received packets. A sender retransmits packets for which no acknowledgement was received within a predefined period of time.

Abstract: A method for reliably communicating unreliable protocol packets by encapsulating one or more unreliable protocol packets in a packet constructed according to a predefined format. The method further employs an acknowledgement mechanism whereby a receiver of packets acknowledges reception by responding with a packet containing information pertaining to received packets. A sender retransmits packets for which no acknowledgement was received within a predefined period of time.