Abstract: A method, computer system, and a computer program product for preemptive collision mitigation is provided. The present invention may include calculating a future position of a first vehicle based on carprobe data from a first vehicle, wherein the carprobe data contains neural data of an operator of the first vehicle. The present invention may also include calculating a distance between the future position of the first vehicle and a future position of a second vehicle. The present invention may then include determining the calculated distance between the future position of the first vehicle and the future position of the second vehicle is below a threshold distance.

Abstract: One embodiment provides a method for augmenting missing values in historical or market data for deals. The method comprises receiving information relating to a set of deals. For any service included in one or more deals of the set of deals but not included in one or more other deals of the set of deals, the method further comprises augmenting, for any or all of the one or more other deals that does not include the service, one or more missing values for the service with one or more recommended values based on a recommendation algorithm. The service may be at any service level of a hierarchy of services.

Abstract: A system and method for scheduling a business process including tasks, comprises a calculation unit, a determination unit, and a decision unit. The calculation unit is configured to calculate an estimated processing time required to execute the tasks. The determination unit is configured to calculate an estimated end time of a route including the tasks on the basis of the estimated processing time and schedule of a user to execute the tasks, and determine whether to apply speculative execution to the business process on the basis of the estimated end time. The decision unit is configured to decide to speculatively execute a task out of the tasks in the business process. The decision is made with reference to a remaining period for executing the task. The remaining period is calculated on the basis of a predicted execution timing of each task and a deadline of the business process.

Abstract: One embodiment provides a method comprising receiving historic peer deals relating to at least one service, and a baseline and cost percentage estimation for each service. Historic peer cost data for each service is clustered to form at least one cluster. Each cluster includes similar unit costs, and has an assigned label. A classification model is trained based on each baseline received, each cost percentage estimation received, and each assigned label. For each assigned label, a corresponding probability distribution is computed based on the classification model. For each service of a new client solution, an assigned label for the service is predicted based on the classification model, and, based on a probability distribution corresponding to the assigned label predicted, transforming an initial range of historic peer cost data relating to the service into a narrower range for use in estimating a cost of the service with improved accuracy.

Abstract: A computational device maintains indications of a plurality of events associated with navigation of a plurality of vehicles in a geographical area. A determination is made as to whether to delete an event from the plurality of events, by performing: transmitting, by an event deletion manager, a query to a plurality of deletion determination agents on whether to delete the event; receiving, by the event deletion manager, an indication from the plurality of deletion determination agents whether to delete the event; and aggregating, by the event deletion manager, indications received from the plurality of deletion determination agents to determine whether to delete the event.

Abstract: Disclosed embodiments provide techniques for generation of vehicle travel data. Past-travel data including previously taken trips, along with metadata including, but not limited to, vehicle type, vehicle model, navigation device model, are obtained and classified. A travel route for simulation data is selected. Data from various previous trips are combined to create a simulation data set for the travel route. This data is based on actual vehicle data. This can enable a new level of accuracy for data analysis and simulations based on this data as compared with purely simulated data. Actual vehicle data accounts for driver behavior, road obstacles, signage, vegetation, vehicle characteristics, and other factors that may not be able to be captured with purely simulated traffic data. Using the data generated by disclosed embodiments enables these factors to be considered in traffic analysis.

Abstract: One embodiment provides a method for augmenting missing values in historical or market data for deals. The method comprises receiving information relating to a set of deals. For any service included in one or more deals of the set of deals but not included in one or more other deals of the set of deals, the method further comprises augmenting, for any or all of the one or more other deals that does not include the service, one or more missing values for the service with one or more recommended values based on a recommendation algorithm. The service may be at any service level of a hierarchy of services.

Abstract: A computational device maintains indications of a plurality of events associated with navigation of a plurality of vehicles in a geographical area. A determination is made as to whether to delete an event from the plurality of events, by performing: transmitting, by an event deletion manager, a query to a plurality of deletion determination agents on whether to delete the event; receiving, by the event deletion manager, an indication from the plurality of deletion determination agents whether to delete the event; and aggregating, by the event deletion manager, indications received from the plurality of deletion determination agents to determine whether to delete the event.

Abstract: One embodiment provides a method for augmenting missing values in historical or market data for deals. The method comprises receiving information relating to a set of deals. For any service included in one or more deals of the set of deals but not included in one or more other deals of the set of deals, the method further comprises augmenting, for any or all of the one or more other deals that does not include the service, one or more missing values for the service with one or more recommended values based on a recommendation algorithm. The service may be at any service level of a hierarchy of services.

Abstract: One embodiment provides a method for top-down pricing of an in-flight deal. The method comprises receiving a first set of information relating to the in-flight deal. The in-flight deal comprises multiple services. The method comprises, for each service of the in-flight deal, selecting a corresponding set of peer deals from historical and market data based on the first set of information, and mining costs for the service from the corresponding set of peer deals. The method further comprises determining a set of price points for the in-flight deal based on each cost mined.

Abstract: A computational device maintains indications of a plurality of events associated with navigation of a plurality of vehicles in a geographical area. A determination is made as to whether to delete an event from the plurality of events, by performing: transmitting, by an event deletion manager, a query to a plurality of deletion determination agents on whether to delete the event; receiving, by the event deletion manager, an indication from the plurality of deletion determination agents whether to delete the event; and aggregating, by the event deletion manager, indications received from the plurality of deletion determination agents to determine whether to delete the event.

Abstract: Generating routes based on aggregated path data includes accumulating trajectory data from a plurality of users, wherein data entries in the trajectory data each include an origin and a destination. When a request for a route from a designated location to a particular destination is received from a particular user, one or more of the data entries are identified as relevant to the request for the route when the origin of a particular data entry is similar to the designated location and the destination of the particular data entry is similar to the particular destination. Route recommendations are generated for the particular user based on one or more data entries identified as relevant.

Abstract: A method, computer system, and a computer program product for preemptive collision mitigation is provided. The present invention may include calculating a future position of a first vehicle based on carprobe data from a first vehicle, wherein the carprobe data contains neural data of an operator of the first vehicle. The present invention may also include calculating a distance between the future position of the first vehicle and a future position of a second vehicle. The present invention may then include determining the calculated distance between the future position of the first vehicle and the future position of the second vehicle is below a threshold distance.

Abstract: Disclosed embodiments provide techniques for generation of vehicle travel data. Past-travel data including previously taken trips, along with metadata including, but not limited to, vehicle type, vehicle model, navigation device model, are obtained and classified. A travel route for simulation data is selected. Data from various previous trips are combined to create a simulation data set for the travel route. This data is based on actual vehicle data. This can enable a new level of accuracy for data analysis and simulations based on this data as compared with purely simulated data. Actual vehicle data accounts for driver behavior, road obstacles, signage, vegetation, vehicle characteristics, and other factors that may not be able to be captured with purely simulated traffic data. Using the data generated by disclosed embodiments enables these factors to be considered in traffic analysis.

Abstract: A system and method for scheduling a business process including tasks, comprises a calculation unit, a determination unit, and a decision unit. The calculation unit is configured to calculate an estimated processing time required to execute the tasks. The determination unit is configured to calculate an estimated end time of a route including the tasks on the basis of the estimated processing time and schedule of a user to execute the tasks, and determine whether to apply speculative execution to the business process on the basis of the estimated end time. The decision unit is configured to decide to speculatively execute a task out of the tasks in the business process. The decision is made with reference to a remaining period for executing the task. The remaining period is calculated on the basis of a predicted execution timing of each task and a deadline of the business process.

Abstract: A system and method for scheduling a business process including tasks, comprises a calculation unit, a determination unit, and a decision unit. The calculation unit is configured to calculate an estimated processing time required to execute the tasks. The determination unit is configured to calculate an estimated end time of a route including the tasks on the basis of the estimated processing time and schedule of a user to execute the tasks, and determine whether to apply speculative execution to the business process on the basis of the estimated end time. The decision unit is configured to decide to speculatively execute a task out of the tasks in the business process. The decision is made with reference to a remaining period for executing the task. The remaining period is calculated on the basis of a predicted execution timing of each task and a deadline of the business process.

Abstract: A hardware computer-implemented method is provided for pricing a current contract for bid that includes generating a tree of the current contract, and generating trees of historical contracts. The contracts each specify respective services. The method includes grouping the trees of historical contracts to form a plurality of groups of trees, based on respective tree distances between the trees in each group. The method includes identifying a group of trees, from the plurality of groups, that is closest to the tree of the current contract by calculating respective distances there between. The method includes calculating a price for the current contract based on gross profits and costs for each service in the identified group. The grouping, identifying, and calculating steps each use different methods, responsive to a service (a) having a baseline; and (b) lacking the baseline, wherein the baseline is a value that indicates a scale of the service.

Abstract: Generating routes based on aggregated path data includes accumulating trajectory data from a plurality of users, wherein data entries in the trajectory data each include an origin and a destination. When a request for a route from a designated location to a particular destination is received from a particular user, one or more of the data entries are identified as relevant to the request for the route when the origin of a particular data entry is similar to the designated location and the destination of the particular data entry is similar to the particular destination. Route recommendations are generated for the particular user based on one or more data entries identified as relevant.

Abstract: One embodiment provides a method for augmenting missing values in historical or market data for deals. The method comprises receiving information relating to a set of deals. For any service included in one or more deals of the set of deals but not included in one or more other deals of the set of deals, the method further comprises augmenting, for any or all of the one or more other deals that does not include the service, one or more missing values for the service with one or more recommended values based on a recommendation algorithm. The service may be at any service level of a hierarchy of services.

Abstract: One embodiment provides a method for top-down pricing of an in-flight deal. The method comprises receiving a first set of information relating to the in-flight deal. The in-flight deal comprises multiple services. The method comprises, for each service of the in-flight deal, selecting a corresponding set of peer deals from historical and market data based on the first set of information, and mining costs for the service from the corresponding set of peer deals. The method further comprises determining a set of price points for the in-flight deal based on each cost mined.