Abstract: A method, computer program product and computer system for recovering from a likely exit condition in an electronic conversation with a user and interactive agent is provided. A processor retrieves one or more messages from a conversation between a user and an interactive agent. A processor determines at least one label for the one or more messages between a user and an interactive agent. A processor compares the at least one label for the one or more messages to a sequence model. A processor identifies the one or more messages from the conversation indicate an exit condition for the user based on the comparison of the at least one label for the one or more messages to the sequence model. A processor sends a recovery message to the user to redirect the conversation.

Abstract: Improving performance of a dialogue-based tutor includes receiving feedback from a user associated with a natural language interaction of the user with a dialogue-based tutoring (DBT) system. The DBT system includes training data and domain-specific content. One or more feedback categories is presented to the user based upon the feedback. A selection of a feedback category from among the one or more feedback categories is received from the user. A feedback candidate is generated based upon the feedback and the selected feedback category. The feedback candidate is indicative of a potential change in one or more of the training data and the domain-specific content based upon the feedback.

Abstract: A method, computer program product and computer system for recovering from a likely exit condition in an electronic conversation with a user and interactive agent is provided. A processor retrieves one or more messages from a conversation between a user and an interactive agent. A processor determines at least one label for the one or more messages between a user and an interactive agent. A processor compares the at least one label for the one or more messages to a sequence model. A processor identifies the one or more messages from the conversation indicate an exit condition for the user based on the comparison of the at least one label for the one or more messages to the sequence model. A processor sends a recovery message to the user to redirect the conversation.

Abstract: Improving performance of a dialogue-based tutor includes receiving feedback from a user associated with a natural language interaction of the user with a dialogue-based tutoring (DBT) system. The DBT system includes training data and domain-specific content. One or more feedback categories is presented to the user based upon the feedback. A selection of a feedback category from among the one or more feedback categories is received from the user. A feedback candidate is generated based upon the feedback and the selected feedback category. The feedback candidate is indicative of a potential change in one or more of the training data and the domain-specific content based upon the feedback.

Abstract: Techniques are disclosed for capturing and visualizing data lineage in content management systems. For example, a method comprises the following steps. A plurality of data sets is received. Each of the data sets is associated with a party and comprises a plurality of information. A set of lineage data about one or more of the data sets is received. The lineage data comprises information about the history of a particular data set. A user interface is presented that conveys a representation of one or more of the plurality of received data sets and at least a portion of the lineage data about the history of one or more of the data sets. A command is received at the user interface to merge or unmerge two data sets in the plurality of data sets. Two or more data sets in the plurality of data sets are merged or unmerged based on the received command.

Abstract: Techniques are disclosed for extracting information through analysis of provenance data. For example, a computer-implemented method of extracting information regarding an execution of an enterprise process comprises the following steps. Provenance data is generated, wherein the provenance data is based on collected data associated with an actual end-to-end execution of the enterprise process and is indicative of a lineage of one or more data items. A provenance graph is generated that provides a visual representation of the generated provenance data, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. At least a portion of the generated provenance data from the graph is analyzed so as to extract information about the execution of the enterprise process based on the analysis.

Abstract: A method of case management includes receiving a plurality of previously executed case instances, receiving a selection of current case attributes and at least one candidate case outcome during runtime of a currently executing case instance, and generating a visual representation of case distributions using the previously executed case instances. The visual representation depicts a correlation between the current case attributes and the at least one candidate case outcome, and is generated using analytics applied to the plurality of previously executed case instances.

Abstract: Techniques are disclosed for capturing, storing, querying and analyzing provenance data for automatic discovery of enterprise process information. For example, a computer-implemented method for managing a process associated with an enterprise comprises the following steps. Data associated with an actual end-to-end execution of an enterprise process is collected. Provenance data is generated based on at least a portion of the collected data, wherein the provenance data is indicative of a lineage of one or more data items. A provenance graph that provides a visual representation of the generated provenance data is generated, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. The generated provenance graph is stored in a repository for use in analyzing the enterprise process.

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 method, system and computer program product for determining health of a case. The method includes the steps of: obtaining at least one correlated trace from (i) task descriptions or (ii) data related to the task descriptions or a process instance; calculating at least one current metric using (i) the task descriptions, (ii) the data, (iii) the correlated trace or (iv) a first model; calculating at least one prognostic metric using a second model; and creating at least one combination metric from the current metric and the prognostic metric; where at least one of the steps is carried out using a computer device.

Abstract: A method, system and article of manufacture are disclosed for configuring software application components. The method comprises the steps of developing a set of policy application rules, assembling unconfigured software components into one or more software applications, and applying said application rules to the unconfigured software components to configure said software components. In the preferred embodiment, the applying step includes the steps of passing the unconfigured software components to a policy rule engine, and using said policy rule engine to apply said application rules to the unconfigured software components to produce the configured components. In addition, the method may be done to resolve ambiguities in the software components. In particular, the application rules may be designed to resolve ambiguities in the application of these rules to the unconfigured software components. Also, each application rule preferably includes a condition, an application template, and a policy.

Abstract: Techniques are disclosed for capturing, storing, querying and analyzing provenance data for automatic discovery of enterprise process information. For example, a computer-implemented method for managing a process associated with an enterprise comprises the following steps. Data associated with an actual end-to-end execution of an enterprise process is collected. Provenance data is generated based on at least a portion of the collected data, wherein the provenance data is indicative of a lineage of one or more data items. A provenance graph that provides a visual representation of the generated provenance data is generated, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. The generated provenance graph is stored in a repository for use in analyzing the enterprise process.

Abstract: Techniques are disclosed for capturing and visualizing data lineage in content management systems. For example, a method comprises the following steps. A plurality of data sets is received. Each of the data sets is associated with a party and comprises a plurality of information. A set of lineage data about one or more of the data sets is received. The lineage data comprises information about the history of a particular data set. A user interface is presented that conveys a representation of one or more of the plurality of received data sets and at least a portion of the lineage data about the history of one or more of the data sets. A command is received at the user interface to merge or unmerge two data sets in the plurality of data sets. Two or more data sets in the plurality of data sets are merged or unmerged based on the received command.

Abstract: Techniques are disclosed for capturing, storing, querying and analyzing provenance data for automatic discovery of enterprise process information. For example, a computer-implemented method for managing a process associated with an enterprise comprises the following steps. Data associated with an actual end-to-end execution of an enterprise process is collected. Provenance data is generated based on at least a portion of the collected data, wherein the provenance data is indicative of a lineage of one or more data items. A provenance graph that provides a visual representation of the generated provenance data is generated, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. The generated provenance graph is stored in a repository for use in analyzing the enterprise process.

Abstract: A pattern-based policy method for service component architecture (SCA) defines a policy pattern for SCA. The policy pattern includes a plurality of roles and one or more constraints between said plurality of roles. Each of said plurality of roles defines a plurality of intents or policy sets or combination thereof. One or more roles assigned to said one or more SCA components are identified and one or more intents or policy sets or combination thereof associated with said one or more roles are automatically applied to said one or more SCA components. Said one or more intents or policy sets or combination thereof applied to said one or more SCA components are validated based on said one or more constraints.

Abstract: Techniques are disclosed for influencing behavior of enterprise operations during process enactment using provenance data. For example, a computer-implemented method of influencing a behavior of an enterprise process comprises the following steps. Provenance data is generated, wherein the provenance data is based on collected data associated with at least a partial actual execution of the enterprise process and is indicative of a lineage of one or more data items. A provenance graph is generated that provides a visual representation of the generated provenance data, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. At least a portion of the generated provenance data from the graph is analyzed to generate an execution pattern corresponding to the at least partial actual execution of the enterprise process. The execution pattern is compared to one or more previously stored patterns.

Abstract: Techniques are disclosed for influencing behavior of enterprise operations during process enactment using provenance data. For example, a computer-implemented method of influencing a behavior of an enterprise process comprises the following steps. Provenance data is generated, wherein the provenance data is based on collected data associated with at least a partial actual execution of the enterprise process and is indicative of a lineage of one or more data items. A provenance graph is generated that provides a visual representation of the generated provenance data, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. At least a portion of the generated provenance data from the graph is analyzed to generate an execution pattern corresponding to the at least partial actual execution of the enterprise process. The execution pattern is compared to one or more previously stored patterns.

Abstract: Techniques are disclosed for extracting information through analysis of provenance data. For example, a computer-implemented method of extracting information regarding an execution of an enterprise process comprises the following steps. Provenance data is generated, wherein the provenance data is based on collected data associated with an actual end-to-end execution of the enterprise process and is indicative of a lineage of one or more data items. A provenance graph is generated that provides a visual representation of the generated provenance data, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. At least a portion of the generated provenance data from the graph is analyzed so as to extract information about the execution of the enterprise process based on the analysis.

Abstract: Techniques are disclosed for capturing, storing, querying and analyzing provenance data for automatic discovery of enterprise process information. For example, a computer-implemented method for managing a process associated with an enterprise comprises the following steps. Data associated with an actual end-to-end execution of an enterprise process is collected. Provenance data is generated based on at least a portion of the collected data, wherein the provenance data is indicative of a lineage of one or more data items. A provenance graph that provides a visual representation of the generated provenance data is generated, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. The generated provenance graph is stored in a repository for use in analyzing the enterprise process.

Abstract: Techniques are disclosed for validating compliance with enterprise operations based on provenance data. For example, a computer-implemented method for validating that an enterprise process is in compliance with a rule comprises the following steps. Provenance data is generated, wherein the provenance data is based on collected data associated with an actual end-to-end execution of the enterprise process and is indicative of a lineage of one or more data items. A provenance graph is generated that provides a visual representation of the generated provenance data, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. A correlation is generated between one or more entities in the rule and one or more record types in the provenance data. One or more control points are generated in accordance with the generated correlation.