International Business Machines Corporation

Sinoeast Concept Limited

Lea A Deleris

Bonnie Kathryn Ray

Eric W Cope

Olivier Verscheure

Adi Ionel Botea

Eric P Bouillet

Kevin Patrick McAuliffe

Shubir Kapoor

Jochen M Kuester

Jana Koehler

Michele Berlingerio

Francesco Calabrese

Chidanand V Apte

Brian F White

Donna Leigh Gresh

Lamia T Bounouane

Bogdan E Sacaleanu

Dominik Etzweiler

A method and computer program product for extending a business process model. The method includes specifying first elements representing performance measures and objectives of a business process which may be compromised by risk events; specifying second elements representing contextual information describing circumstances which may be relevant to a failure mode of the process, said contextual information comprising a type and state of: resources to support the process, of jobs and artifacts that undergo the process; and, a type and state of environmental factors; specifying third elements representing errors which may occur during process execution; specifying fourth elements representing causal relationships among risk events related to the resources, activities, and said environmental factors that may influence process execution; and providing a set of metamodel extensions to a standard process modeling language that incorporate said specified first second third and fourth elements directly in the business process model.

Method for creating and expressing risk-extended business process models

Embodiments of the disclosure include a method for journey planning including receiving a journey planning request, the journey planning request having an origin and a destination in a transportation network. The method also includes calculating an optimized journey plan by identifying a plurality of routes through the transportation network from the origin to the destination and determining an uncertainty associated with each of the plurality of routes. Calculating an optimized journey plan also includes evaluating a robustness of each of the plurality of routes to the uncertainty associated with each of the plurality of routes and selecting the optimized journey plan based on the journey planning request and the robustness of each of the plurality of routes.

Hedging risk in journey planning

A system and computer program product that facilitates authoring of a Bayesian Belief Networks by: accessing text content stored in a content storage device; identifying statements within said accessed text content indicating a dependence relation; extracting said statements indicating said dependence relation from said text content; and aggregating said extracted statements into a form suitable for representation as a BBN network structure. To identify statements indicating a dependence relation, the system identifies one or more lexical and semantic attributes of variables within a text unit indicating a conditional dependence relation between two or more variables. The system further processes the text content to extract probabilistic information and probability statements and aggregate the probability statements into a quantitative layer of the BBN structure.

Authoring system for bayesian networks automatically extracted from text

Embodiments of the disclosure include a computer system for journey planning, the computer system includes a journey planning server configured to perform a method. The method includes receiving a journey planning request, the journey planning request having an origin and a destination in a transportation network. The method also includes calculating an optimized journey plan by identifying a plurality of routes through the transportation network from the origin to the destination and determining an uncertainty associated with each of the plurality of routes. Calculating an optimized journey plan also includes evaluating a robustness of each of the plurality of routes to the uncertainty associated with each of the plurality of routes and selecting the optimized journey plan based on the journey planning request and the robustness of each of the plurality of routes.

A system and method that facilitates authoring of a Bayesian Belief Networks by: accessing text content stored in a content storage device; identifying statements within said accessed text content indicating a dependence relation; extracting said statements indicating said dependence relation from said text content; and aggregating said extracted statements into a form suitable for representation as a BBN network structure. To identify statements indicating a dependence relation, the method includes identifying one or more lexical and semantic attributes of variables within a text unit indicating a conditional dependence relation between two or more variables. The method further processes the text content to extract probabilistic information and probability statements and aggregate the probability statements into a quantitative layer of the BBN structure.

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.

System and method for creating and expressing risk-extended business process models

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.

Method and system enabling dynamic composition of heterogenous risk models

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.

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White Plains, NY, United States of America

Lea A Deleris