Abstract: Aspects include a computer-implemented method comprising tracking of one or more actions (e.g., patient actions) carried out on a web-based computing platform that enables text, audio, video and/or any other communication between providers and their clients, and aggregating indicators of at least one of these actions into a score calculated at one or more measurement intervals. Calculated scores may be compared to one or more reference scores. An action may be triggered based on a calculated score and/or based on the relative values of a calculated score and a reference score.

Abstract: Aspects include a computer-implemented method comprising tracking of one or more actions (e.g., patient actions) carried out on a web-based computing platform that enables text, audio, video and/or any other communication between providers and their clients, and aggregating indicators of at least one of these actions into a score calculated at one or more measurement intervals. Calculated scores may be compared to one or more reference scores. An action may be triggered based on a calculated score and/or based on the relative values of a calculated score and a reference score.

Abstract: A computing system initializes a first frontier to be a root of a multi-dimensional hierarchical data structure representing an entity. The system acquires first data corresponding to the first frontier. The system performs modeling on the first data to obtain a first model and a corresponding first statistic. The system expands a dimension of the first frontier. The system gathers second data corresponding to the expanded frontier. The system applies the data modeling on the second data to obtain a second model and a corresponding second statistic. The system compares the first statistic of the first model and the second statistic of the second model. The system sets the second model to be the first model in response to determining that the second model statistic is better than the first model statistic. The system outputs the first model.

Abstract: A method and computer program product for extending a business process model.

Abstract: A method for determining a policy that considers observations delayed at runtime is disclosed. The method includes constructing a model of a stochastic decision process that receives delayed observations at run time, wherein the stochastic decision process is executed by an agent, finding an agent policy according to a measure of an expected total reward of a plurality of agent actions within the stochastic decision process over a given time horizon, and bounding an error of the agent policy according to an observation delay of the received delayed observations.

Abstract: A method, computer storage medium, computer system of performing monitor deployment under budget constraints includes obtaining a network topology and a deployment budget, decomposing the network topology into a plurality of components having a predetermined property, computing a benefit and a cost for identifying each of the components, selecting at least one targeted component based on a ratio of the benefit to the cost for identifying each of the components, and deploying monitors to identify links in the at least one targeted component within a remaining portion of the deployment budget.

Abstract: The present disclosure relates generally to mechanisms for bounded-budget monitor deployment in monitoring networks via end-to-end probes. In various embodiments, methodologies may be provided that automatically perform bounded-budget monitor deployment in monitoring networks via end-to-end probes.

Abstract: A system, method and computer program product for facilitating collaborative decision making may be provided. The system receives data representing individual postings of users associated with a deliberation to make a decision. The system further receives ratings associated with the individual postings in order to make the decision. The system represents the received data in a hierarchical data structure. The system aggregates, through the hierarchical data structure, the ratings associated with the individual postings to obtain strength values. The system facilitates the making of the decision based on the aggregated strength values.

Abstract: A method (and corresponding computer readable storage medium) of selective monitor deployment under budget constraints, wherein the mechanism includes iterating through each layer of an overlay network multiple times and wherein monitor deployment in a lower layer results in recommending adjustments of monitor deployment in an upper layer so as to reduce the overall deployment cost. Also, a method (and corresponding computer readable storage medium) of selective monitor deployment under budget constraints, wherein a deployment budget is a residual budget after deployment at higher layers of an overlay network.

Abstract: A method including, for a set of historical and/or ongoing business initiatives, determining key negative and positive performance factors by a computer from a structured taxonomy of negative and positive performance factors stored in a memory; modeling at least one of the performance factors for the ongoing business initiative or a new business initiative at at least one level of the hierarchical taxonomy. The key negative and positive performance factors are modeled based, at least partially, upon a likelihood of occurrence of the key negative performance factors during the business initiative, and based, at least partially, upon potential impact of the key performance factors on the business initiative. The method further includes providing the modeled performance factors in a report to a user, where the report identifies the modeled performance factors, and the potential impact of the at least one modeled performance factor.

Abstract: One or more processors determine a financial target for a plurality of business accounts across a plurality of product brands that are included in a business account level of an organizational hierarchy of a business organization. The organizational hierarchy includes a plurality of levels. One or more processors determine respective financial targets and quotas for a plurality of nodes included in a level of the organizational hierarchy. One or more processors determine respective financial targets for combinations of business accounts and product brands. The determination of the financial targets is based on a statistical model that is fitted at a middle level of the organizational hierarchy, and a risk-based stochastic optimization that is used to set financial targets and quotas at one or more levels of the organizational hierarchy.

Abstract: A system, method and computer program product for facilitating collaborative decision making may be provided. The system receives data representing individual postings of users associated with a deliberation to make a decision. The system further receives ratings associated with the individual postings in order to make the decision. The system represents the received data in a hierarchical data structure. The system aggregates, through the hierarchical data structure, the ratings associated with the individual postings to obtain strength values. The system facilitates the making of the decision based on the aggregated strength values.

Abstract: The present disclosure relates generally to mechanisms for bounded-budget monitor deployment in monitoring networks via end-to-end probes. In various embodiments, methodologies may be provided that automatically perform bounded-budget monitor deployment in monitoring networks via end-to-end probes.

Abstract: A method and computer program product for extending a business process model.

Abstract: A method and computer program product for integrating risk management concepts into a standard business process metamodel by defining a set of metamodel extensions to standard process modeling languages that incorporate risk information directly in the process model. The method includes collecting risk-relevant information for addition to a business process model, and enabling visualizing of a risk-extended business process model. using a notation to express notions as failure modes of resources, root cause events, and sources of execution failure and low job output quality directly in the context of process models. Additionally, the method enables the computation of risk-related impacts on the distribution of process performance measures using a Bayesian network model or a discrete-event simulation model.

Abstract: A method and system for quantifying risk by composing a heterogeneous risk model are provided. The method comprises providing risk input data associated with one or more risk nodes to a processor, running one or more risk models to output individual risk quantifications for each risk node, and aggregating the individual risk quantifications into a single output. The system comprises a processor operable to provide risk input data associated with one or more risk nodes to a processor, run one or more risk models to output individual risk quantifications for each risk node and aggregate the individual risk quantifications into a single output.

Abstract: A method and system for collaboratively managing risk is presented. In one embodiment the method comprises analyzing a node in a risk network when an output of said node violates a control limit, identifying a cause of said violation of said control limit, creating a mitigation action in response to said node violating said control limit, performing said mitigation action, said mitigation action having an influence on said output of said node, and measuring said output of said node to determine effectiveness of said mitigation action on said node, wherein a program using a processor unit executes one or more of said analyzing, identifying, creating, performing and measuring steps.

Abstract: A computing system initializes a first frontier to be a root of a multi-dimensional hierarchical data structure representing an entity. The system acquires first data corresponding to the first frontier. The system performs modeling on the first data to obtain a first model and a corresponding first statistic. The system expands a dimension of the first frontier. The system gathers second data corresponding to the expanded frontier. The system applies the data modeling on the second data to obtain a second model and a corresponding second statistic. The system compares the first statistic of the first model and the second statistic of the second model. The system sets the second model to be the first model in response to determining that the second model statistic is better than the first model statistic. The system outputs the first model.

Abstract: A method and system for collaboratively managing risk is presented. In one embodiment the method comprises analyzing a node in a risk network when an output of said node violates a control limit, identifying a cause of said violation of said control limit, creating a mitigation action in response to said node violating said control limit, performing said mitigation action, said mitigation action having an influence on said output of said node, and measuring said output of said node to determine effectiveness of said mitigation action on said node, wherein a program using a processor unit executes one or more of said analyzing, identifying, creating, performing and measuring steps.

Abstract: An online recommendation system, method and computer program product for recommending on-line item(s) including a recommended a usage for the on-line item(s).