System and method for analyzing data
First Claim
1. A system for analyzing data, said system including a processor and memory and comprising:
- a data subsystem, including a plurality of template data points and an input file, said input file comprising a plurality of analysis data points;
an interface subsystem, including a plurality of input characteristics and a plurality of events, wherein said interface subsystem creates said events from at least one said input characteristic and at least one of the plurality of template data points, wherein at least one said event is stored in a pattern array, wherein a subset of said plurality of data points are stored in a data array, and wherein a correlation heuristic is applied to said pattern array and said data array to identify a marker location; and
an analysis subsystem, including a plurality of markers, wherein said analysis subsystem searches said data subsystem for said analysis data points indicative of at least a portion of said events, and wherein said analysis subsystem places said markers on said analysis data points within the input file indicative of said events without human intervention, wherein said markers are placed at a plurality of marker locations, wherein said marker locations are identified by a correlation-based matching heuristic, and wherein a confidence value is associated with the identification of each said marker locations.
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Accused Products
Abstract
A system and method for analyzing data (the “system”) is disclosed. The system can automatically identify patterns of template data points encapsulated in the form of one or more “events.” Calculations and analysis relating to those identified events can be automatically performed at the identified locations of the events. Events are user-defined, and can be defined in reference to multiple channels of data. The system can perform various correlation calculations in comparing events with data points. Upon identifying the location of various events in the various data files, markers can be placed at those file locations. Analysis calculations can then be performed related to the marked data. The system can incorporate the automated time-scaling of patterns, marker sorting heuristics, the adjustment of fit sensitivity based on the size of the pattern, target value weighing, and the calculation of various confidence values relating to the processing of the system.
75 Citations
36 Claims
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1. A system for analyzing data, said system including a processor and memory and comprising:
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a data subsystem, including a plurality of template data points and an input file, said input file comprising a plurality of analysis data points; an interface subsystem, including a plurality of input characteristics and a plurality of events, wherein said interface subsystem creates said events from at least one said input characteristic and at least one of the plurality of template data points, wherein at least one said event is stored in a pattern array, wherein a subset of said plurality of data points are stored in a data array, and wherein a correlation heuristic is applied to said pattern array and said data array to identify a marker location; and an analysis subsystem, including a plurality of markers, wherein said analysis subsystem searches said data subsystem for said analysis data points indicative of at least a portion of said events, and wherein said analysis subsystem places said markers on said analysis data points within the input file indicative of said events without human intervention, wherein said markers are placed at a plurality of marker locations, wherein said marker locations are identified by a correlation-based matching heuristic, and wherein a confidence value is associated with the identification of each said marker locations. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 31, 32, 33, 34, 35)
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20. A system for analyzing data, said system including a processor and memory and comprising:
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a data subsystem, including a plurality of data types and plurality of files comprising a plurality of analysis data points, wherein each said analysis data point is associated with at least one said data type; a pattern subsystem, including a plurality of events, a plurality of input characteristics, and a plurality of template data points, wherein said events are defined from said input plurality of characteristics, and wherein at least two said template data points are associated with each said event, wherein at least one said event is stored in a pattern array, wherein a subset of said plurality of data points are stored in a data array, and wherein a correlation heuristic is applied to said pattern array and said data array to identify a marker location; and a search subsystem, including a plurality of markers, wherein said search subsystem identifies a plurality of locations indicative of at least a portion of said events within said data subsystem, and wherein said analysis subsystem places said markers on said analysis data points within the input file indicative of said events without human intervention, and wherein said markers are placed at a plurality of marker locations, wherein said marker locations are identified by a correlation-based matching heuristic, and wherein a confidence value is associated with the identification of each said marker locations. - View Dependent Claims (21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 36)
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Specification