Abstract: Embodiments for discovery and analysis of interpersonal relationships from a collection of unstructured text data by a processor. A relationship between one or more entities and extracted text data from a plurality of unstructured text data may be identified such that the relationship includes a sentiment of the relationship, a type of relationship, temporal information, or a combination thereof. The one or more entities may be associated with a knowledge graph based on an ontology of concepts representing a domain knowledge. The extracted information and the identified relationship may be automatically aggregated into a multi-graph representation.

Abstract: Embodiments for semantic hierarchical grouping of short text fragments by a processor. Sub-terms are extracted from a plurality of input text fragments according to a lexical sub-term hierarchy. Each of the sub-terms in the lexical sub-term hierarchy are matched with concepts based on an ontology of concepts representing a domain knowledge. The input text fragments are automatically grouped into a hierarchy of concepts based on the matching and a semantical relationship between each concept and matching sub-term.

Abstract: There is provided a method, a system and a computer program product for supporting a decision making process. The system receives a decision model from a decision maker, the decision model used for determining a solution to a decision problem based on attributes and uncertainties of the decision problem. The decision problem includes information about a plurality of outcome vectors that represent all possible outcomes and the uncertainties associated with the decision problem. The system determines whether the received decision model can be solved without receiving any preference information from the decision maker. The system receives partially specified preference information from the decision maker if the received decision model cannot be solved without any preference information. The system solves the decision model with the partially specified preference information. The system recommends, based on the solution, one or more decisions to the decision maker.

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

Abstract: 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.

Abstract: 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.

Abstract: There is provided a method, a system and a computer program product for supporting a decision making process. The system receives a decision model from a decision maker, the decision model used for determining a solution to a decision problem based on attributes and uncertainties of the decision problem. The decision problem includes information about a plurality of outcome vectors that represent all possible outcomes and the uncertainties associated with the decision problem. The system determines whether the received decision model can be solved without receiving any preference information from the decision maker. The system receives partially specified preference information from the decision maker if the received decision model cannot be solved without any preference information. The system solves the decision model with the partially specified preference information. The system recommends, based on the solution, one or more decisions to the decision maker.

Abstract: There is provided a method, a system and a computer program product for supporting a decision making process. The system receives a decision model from a decision maker, the decision model used for determining a solution to a decision problem based on attributes and uncertainties of the decision problem. The decision problem includes information about a plurality of outcome vectors that represent all possible outcomes and the uncertainties associated with the decision problem. The system determines whether the received decision model can be solved without receiving any preference information from the decision maker. The system receives partially specified preference information from the decision maker if the received decision model cannot be solved without any preference information. The system solves the decision model with the partially specified preference information. The system recommends, based on the solution, one or more decisions to the decision maker.

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: There is provided a method, a system and a computer program product for supporting a decision making process. The system receives a decision model from a decision maker, the decision model used for determining a solution to a decision problem based on attributes and uncertainties of the decision problem. The decision problem includes information about a plurality of outcome vectors that represent all possible outcomes and the uncertainties associated with the decision problem. The system determines whether the received decision model can be solved without receiving any preference information from the decision maker. The system receives partially specified preference information from the decision maker if the received decision model cannot be solved without any preference information. The system solves the decision model with the partially specified preference information. The system recommends, based on the solution, one or more decisions to the decision maker.

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: 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.

Abstract: 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.

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 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 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 the distributed elicitation and aggregation of risk information is provided. The method comprises selecting a risk network, the risk network comprising one or more risk nodes having associated risk information; assigning a role to each risk node, said role indicating a type of user to evaluate the risk node; generating a customized survey to elicit risk information for a risk node based upon the role and the user, wherein an order of questions in the customized survey presented to the user is determined by an ordering criteria; publishing the customized survey to the user; collecting risk information for the risk node from the user's answers to the customized survey; and populating the risk nodes based on the collected risk information.

Abstract: A computer implemented method for improving project risk management based on (a) a quantitative analysis of risks affecting activities, i.e., the root factors leading to cost and time overruns on an activity by activity basis, and (b) an optimization of the resources allocation to each activity in the project plan, is employed to maximize the probability of completing projects on time and within-budget. The method can be employed prior to proceeding with one or more projects, but is also advantageous in that it is adaptive in the sense that more information can be learned during the course of a project about the risk factors present in the project, and this information is used to enable dynamically re-allocating resources to ensure a better outcome given an updated risk profile. Preferably, a Bayesian Belief Network (BBN) is used to capture how risk factors identified by project managers influence individual activity durations.