Abstract: Provided are improved systems, methods, and computer programs to facilitate predictive accuracy for strategic decision support using a query specific Bayesian network. An unconstrained domain model is defined by domain concepts and causal relationships between the domain concepts. Each causal relationship includes a value for the weight of causal belief for the causal relationship. In response to a query, the unconstrained domain model is transformed into a query specific Bayesian network for the domain model by identifying one or more cycles in the unconstrained domain model, eliminating the one or more cycles from the unconstrained domain model; identifying a sub-graph of the unconstrained domain model that is relevant to a query and creating one or more conditional probability tables that comprise the query specific Bayesian network.

Abstract: According to an embodiment, a computer-implemented method of identifying delay causing product assembly jobs in a factory that produces multiple products includes acquiring delay times for each of a plurality of jobs performed for assembly of each of a plurality of products at the factory, ranking the jobs according to a number of products affected by delay times, whereby a ranked jobs list is produced, adjusting at least one of a delay threshold, a job rank threshold, or a number of products threshold until a plot of amount of products affected by a delay exceeding the delay threshold as a dependent variable, versus ranked jobs of the ranked jobs list as an independent variable, exceeds the number of products threshold at the job rank threshold, and outputting an initial segment of the ranked jobs list up to the job rank threshold.

Abstract: Provided are improved systems, methods, and computer programs to facilitate predictive accuracy for strategic decision support using a query specific Bayesian network. An unconstrained domain model is defined by domain concepts and causal relationships between the domain concepts. Each causal relationship includes a value for the weight of causal belief for the causal relationship. In response to a query, the unconstrained domain model is transformed into a query specific Bayesian network for the domain model by identifying one or more cycles in the unconstrained domain model, eliminating the one or more cycles from the unconstrained domain model; identifying a sub-graph of the unconstrained domain model that is relevant to a query and creating one or more conditional probability tables that comprise the query specific Bayesian network.

Abstract: Systems and methods of recommending replacement of parts on machines. In one embodiment, a method of recommending replacement includes receiving data for a part type, determining a cumulative probability function for an infant mortality of the part type, and determining a cumulative probability function for a natural life of the part type. The method includes defining a lower time boundary and an upper time boundary between which the part type is considered operative. The lower time boundary is defined at a time point at an intersection between the cumulative probability function for the infant mortality and the cumulative probability function for the natural life of the part type. The upper time boundary is defined at a time point representing an estimated end of an operative life of the part type. Recommending replacement of a part on a machine may then be determined based on the upper and lower time boundaries.

Abstract: Devices and methods for use in forecasting the state of one or more of a plurality of variables within a domain are provided. One example method includes determining, at a processor, a first probability curve indicative of a probability of a change-in-state of the first variable over a first interval, the first probability defining a first substantially continuous time trajectory, determining, at the processor, a second probability curve indicative of a probability of a change-instate of the second variable over a second interval, the second probability defining a second substantially continuous time trajectory, the first interval at least partially overlapping with the second interval, and displaying, at a display device, the first and second probability curves substantially in real time, thereby permitting a user to compare the relative probabilities of the change-in-state of at least one of the first and second variables.

Abstract: Provided are improved systems, methods, and computer programs to facilitate predictive accuracy for strategic decision support using Continuous Time Bayesian Networks. A simple semantic is provided for both probabilistic and temporal relationships that can be automatically translated into functioning Bayesian and Continuous Time Bayesian Network formalisms and applied by a user for reasoning analysis, such as to assess a hypothesis or respond to a query with a probabilistic and temporal prediction of a future event.

Abstract: The present invention relates to a system and methodology to facilitate collaboration and communications between entities such as between automated applications, parties to a communication and/or combinations thereof. The systems and methods of the present invention include a service that supports collaboration and communication by learning predictive continuous time Bayesian models that provide forecasts of one or more aspects of a users' presence and availability. Presence forecasts include a user's current or future locations at different levels of location precision and usage of different devices or applications. Availability assessments include inferences about the cost of interrupting a user in different ways and a user's current or future access to one or more communication channels.