Abstract: Systems and methods for data analysis include constructing patient traces as a set of medical events for each patient of a patient population, the patient population being segmented based on patient outcomes. Medical events in one or more of the patient traces are reduced to provide processed patient traces. The processed patient traces are clustered to identify a cluster of patient traces. A process model is mined, using a processor, representing an aggregation of treatment pathways in the patient traces from the cluster. Patterns from patient traces are identified that are discriminative of patient outcomes. At least one of the patterns is represented with respect to the process model to identify treatment pathways correlated with the patient outcomes.

Abstract: Systems and methods for data analysis include correlating event data to provide process instances. The process instances are clustered, using a processor, by representing the process instances as strings and determining distances between strings to form a plurality of clusters. One or more metrics are computed on the plurality of clusters to monitor deviation of the event data.

Abstract: A method, system and computer program product for simplifying a plurality of correlation rules of a graph. The method includes the steps of: receiving correlation rules; creating an undirected graph; removing redundant edges from the undirected graph; splitting nodes in the undirected graph; replacing a probability that an edge that connects two nodes to a seed value; modifying the seed value by adding a first value to said seed value and adding a second value to the first value; determining a maximum modified seed value; adding the maximum modified seed value to a probability that the uncertain edge connects two nodes; removing any temporary certain edge; and running a minimum spanning tree algorithm on said modified undirected graph.

Abstract: An analyzer system may include a computer-apparatus to collect traces from a pool of business traces, and to assign an unique vector value to each trace. The system may also include an assembler to create a tree based upon the unique vector value of each trace. The system may further include an analyzer to detect sub-trees within the tree to identify similarities among the traces based upon the traces inclusion within a given sub-tree.

Abstract: An analyzer system may include a computer-apparatus to collect traces from a pool of business traces, and to assign an unique vector value to each trace. The system may also include an assembler to create a tree based upon the unique vector value of each trace. The system may further include an analyzer to detect sub-trees within the tree to identify similarities among the traces based upon the traces inclusion within a given sub-tree.

Abstract: A method, system and computer program product for simplifying a plurality of correlation rules of a graph. The method includes the steps of: receiving correlation rules; creating an undirected graph; removing redundant edges from the undirected graph; splitting nodes in the undirected graph; replacing a probability that an edge that connects two nodes to a seed value; modifying the seed value by adding a first value to said seed value and adding a second value to the first value; determining a maximum modified seed value; adding the maximum modified seed value to a probability that the uncertain edge connects two nodes; removing any temporary certain edge; and running a minimum spanning tree algorithm on said modified undirected graph.

Abstract: A system for visualizing a process includes a trace manager receiving a plurality of trace sets, each trace set having a plurality of business process execution traces, each of the business process execution traces being a representation of an individual work flow, a model generator creating a model from each of the trace sets, each model being a directed graph including a work flow of an aggregate of the business process execution traces in a respective trace set, a model comparator extracting a plurality of differences between the models and creating a comparison result based on the plurality of differences, wherein the comparison result is stored to a collaborative system, and a trace set identifier configured to identify a subset of the trace set based on a selected subsection of the model, where the subset of trace set exhibits at least one difference extracted from the selected subsection of the model.

Abstract: A computer-implemented method, system, and article of manufacture for extracting and processing event data from heterogeneous computer applications. The method includes providing a computer system having software modules for performing the steps of: receiving data related to a first event; identifying a data type of the first event based on data type definitions; selecting a set of extraction rules for extracting an attribute of an event having the identified data type; extracting the first attribute from the first event data based on the set of extraction rules; and mapping the first attribute to an event attribute of a unified structure.

Abstract: A computer-implemented method, system, and article of manufacture for determining a set of correlated data among heterogeneous computer applications. The method includes providing a computer system having software modules, receiving statistics on data relating to a first event and a second event, generating a confidence score for an attribute set, where the attribute set includes an attribute from the first event data and an attribute from the second event data, and selecting the attribute set as a set of correlated data if the confidence score is within a threshold value.

Abstract: A computer-implemented method, system, and article of manufacture for extracting and processing event data from heterogeneous computer applications. The method includes providing a computer system having software modules for performing the steps of: receiving data related to a first event; identifying a data type of the first event based on data type definitions; selecting a set of extraction rules for extracting an attribute of an event having the identified data type; extracting the first attribute from the first event data based on the set of extraction rules; and mapping the first attribute to an event attribute of a unified structure.

Abstract: A computer-implemented method, system, and article of manufacture for determining a set of correlated data among heterogeneous computer applications. The method includes providing a computer system having software modules, receiving statistics on data relating to a first event and a second event, generating a confidence score for an attribute set, where the attribute set includes an attribute from the first event data and an attribute from the second event data, and selecting the attribute set as a set of correlated data if the confidence score is within a threshold value.

Abstract: A method of processing a source set of raw events of unknown event types to a target set of typed events, each raw event being a package of data items containing data values of detectable data types, includes the steps of: providing a library of event type objects each of which relates to a given event type and contains a structured set of attributes of given data types; for each raw event, determining at least one event type object in the library which meets the following criteria: (i) the data items of the raw event can each be mapped to one of the attributes of said event type object, and (ii) the detected data types of the raw event each match the given data type of the respective attribute mapped; and generating a typed event from the raw event by structuring the data values of the raw event in the form of the event type object determined.