Abstract: Systems and methods for incident detection are provided. A system for incident detection comprises a network including at least one detector for detecting events in the network, a detection module capable of processing data from the at least one detector, and a calibration module capable of calibrating a plurality of bands for the incident detection based on a plurality of decision variables, wherein the plurality of bands define thresholds that are time-varying for all measurement locations in the network, and the thresholds are estimated using nonparametric quantile regression.

Abstract: Systems and methods for incident detection are provided. A system for incident detection comprises a network including at least one detector for detecting events in the network, a detection module capable of processing data from the at least one detector, and a calibration module capable of calibrating a plurality of bands for the incident detection based on a plurality of decision variables, wherein the plurality of bands define thresholds that are time-varying for all measurement locations in the network, and the thresholds are estimated using nonparametric quantile regression.

Abstract: Search results are received that were generated by a search engine in response to a search query entered by a user. The search results include a first result which contains a first set of identifying data. The first result is matched with a first profile on a first social network which is merged with a second social network. The first profile contains a second set of identifying data which satisfies matching criteria for similarity with the first set of identifying data.

Abstract: A method and structure of estimating traffic in a network. A real-time estimate of the network traffic is calculated, based on limited real-time data about the network traffic calculated in an offline phase and limited real-time data received in a real-time phase.

Abstract: A prediction modeling system and computer program product for implementing forecasting models that involve numerous measurement locations, e.g., urban occupancy traffic data. The system a data volatility reduction technique based on computing a congestion threshold for each prediction location, and using that threshold in a filtering scheme. Through the use of calibration, and by obtaining an extremal or other specified solution (e.g., maximization) of empirical volume-occupancy curves as a function of the occupancy level, significant accuracy gains are achieved and at virtually no loss of important information to the end user. The calibration use quantile regression to deal with the asymmetry and scatter of the empirical data. The argmax of each empirical function is used in a unidimensional projection to essentially filter all fully congested occupancy level and treat them as a single state.

Abstract: A method and apparatus for predicting traffic on a transportation network where real time data points are missing. In one embodiment, the missing data is estimated using a calibration model comprised of historical data that can be periodically updated, from select links constituting a relationship vector. The missing data can be estimated off-line whereafter it can be used to predict traffic for at least a part of the network, the traffic prediction being calculated by using a deviation from a historical traffic on the network. The invention further discloses a method for in-vehicle navigation; and a method for traffic prediction for a single lane.

Abstract: A system, method and computer program product for forecasting a vehicle traffic condition in a near future. The system comprises a traffic prediction tool, a turning percentage prediction module and a simulation tool. The traffic prediction tool estimates a traffic speed and volume in a traffic link. A traffic link refers to a portion of a traffic road where the traffic prediction tool is installed. The turning percentage prediction module estimates a turning percentage in the traffic link based on the estimated traffic speed and traffic volume. The simulation tool computes, based on the estimated turning percentage, the estimated traffic speed and the estimated traffic volume, an expected traffic volume in the traffic link.

Abstract: Yield management techniques are provided. In one aspect of the invention, a technique for managing one or more computing resources comprises the following steps/operations. Data associated with at least one potential demand for use of the one or more computing resources is obtained. Then, a management model (e.g., a yield management model or a revenue management model) is generated in accordance with at least a portion of the obtained data, wherein the management model is operative to determine an allocation of the one or more computing resources based on combinations of price levels and service levels that may be offered to one or more users of the one or more computing resources so as to attempt to satisfy at least one management goal.

Abstract: A method and apparatus for predicting traffic on a transportation network where real time data points are missing. In one embodiment, the missing data is estimated using a calibration model comprised of historical data that can be periodically updated, from select links constituting a relationship vector. The missing data can be estimated off-line whereafter it can be used to predict traffic for at least a part of the network, the traffic prediction being calculated by using a deviation from a historical traffic on the network. The invention further discloses a method for in-vehicle navigation; and a method for traffic prediction for a single lane.

Abstract: A system, method and computer program product for obtaining a traffic route for a vehicle. The system receives information of a current location of the vehicle. The system determines a destination location or destination region of the vehicle. The system computes a plurality of available traffic routes from the current location to the destination location or to the destination region. The system estimates a potential demand for at least one potential passenger from the current location to the destination location or to the destination region per each available traffic route. The system recommends, to a driver of the vehicle, an available traffic route that has a highest estimated potential demand among a plurality of the available traffic routes.

Abstract: A method, system and computer program product for allocating network resources. In one embodiment, a service provider allocates an amount of the network resources to a group of clients, and the service provider receives a request from a client for a quantity of the network resources. The service provider negotiates with the group of clients and offers the group of clients an incentive to reduce the amount of the network resources allocated to this group of clients. The service provider reallocates some of the resources from the group of clients, based on this negotiating, to accommodate the request. In this embodiment, each of the group of clients provides a business value representing a value that would be lost due to reductions in the resources allocated to the each client, and the resources are reallocated based on this business values provided by the group of clients.

Abstract: A method and structure for reducing customer dissatisfaction for waiting includes a queue monitoring subsystem which detects an entry of a customer into a waiting queue. A reward computing subsystem calculates a reward for the customer for being in the waiting queue, and a communication subsystem communicates the reward to the customer. At least one of subsystems is automated.

Abstract: The present disclosure relates generally to real-time traffic prediction and/or estimation using GPS data with low sampling rates. In various examples, real-time traffic prediction and/or estimation using GPS data with low sampling rates may be implemented in the form of systems, methods and/or algorithms.

Abstract: System and methods provide decision support by receiving suggested actions from a decision support system and automatically determining parameters of the suggested actions to serve as input to a question-answering system. System and methods also automatically generate questions based on the parameters, automatically search a corpus of unstructured data to retrieve answers to the questions, and automatically provide impact confidence values for each answer indicating the degree of impact the answers have on the suggested actions. The systems and methods can then output the questions, answers, and impact confidence values.

Abstract: A method, an apparatus and an article of manufacture for incident duration prediction. The method includes obtaining incident data for at least one traffic-related incident in a selected geographic area, obtaining traffic data for the selected geographic area, spatially and temporally associating the at least one traffic-related incident with the traffic data to generate incident duration data for the at least one traffic-related incident, and predicting incident duration of at least one additional traffic-related incident based on the incident duration data for the at least one traffic-related incident.

Abstract: A method of informing sales strategies using a social network includes receiving an input from an organization, wherein the input comprises information relating to an item for sale, extracting sales data from a first database, event history data from a second database, and action history data from a third database, wherein the sales data represents past sales of the item, the event history data represents past events, and the action history data represents past actions taken by the organization, establishing a connection with the social network via a communication network, monitoring a real-time data stream via the connection to the social network for mentions relating to the item, and generating an action recommendation relating to the item based on the sales data, event history data, action history data, and mentions relating to the item.

Abstract: Systems and methods are provided to determine an allocation of network resources in a distributed on-demand information technology (IT) systems using existing control mechanisms for other operating system resources in order to achieve a desired operating point within the IT system. This desired operating point is obtained by optimizing a goal-based objective function while taking into account system constraints. The relationship between utilization of all system resources, i.e. network resources and processing resources, and attainment of performance objectives is autonomously obtained for a plurality of actions that could be required by a range of system applications. This relationship is used to allocate network resources to applications while maintaining desired performance objectives. The allocation is enforced using existing control mechanisms.

Abstract: A decision support for real time command center, in one aspect, classifies, using a decision tree, an observed network state of a network into at least one category. A meta-model associated with the classified at least one category may be selected from a plurality of meta-models, the plurality of meta-models having been calibrated using results of simulations of a plurality of scenarios occurring in the network. One or more action plans may be evaluated by running the selected meta-model with data of the observed network state. One or more recommended action plans may be generated for the real time command center, based on the evaluation. Actual network state data resulting from having applied the one or more recommended action plans may be evaluated and used to recalibrate the meta-model and/or the decision tree.

Abstract: A method of choosing jobs to run in a stream based distributed computer system includes determining jobs to be run in a distributed stream-oriented system by deciding a priority threshold above which jobs will be accepted, below which jobs will be rejected. Overall importance is maximized relative to the priority threshold based on importance values assigned to all jobs. System constraints are applied to ensure jobs meet set criteria.

Abstract: System and methods provide decision support by receiving suggested actions from a decision support system and automatically determining parameters of the suggested actions to serve as input to a question-answering system. System and methods also automatically generate questions based on the parameters, automatically search a corpus of unstructured data to retrieve answers to the questions, and automatically provide impact confidence values for each answer indicating the degree of impact the answers have on the suggested actions. The systems and methods can then output the questions, answers, and impact confidence values.