Abstract: A method for managing user information streams associated with recommendation systems based on cognitively counter-matched mined content is provided. The method may include determining and extracting first concepts from mined content. The method may further include determining second concepts associated with the determined and extracted, wherein the second concepts comprise one or more different interpretations of the first concepts. The method may further include determining relationships between the second concepts by analyzing the second concepts using data mining analysis techniques. The method may further include, based on the determined one or more relationships between the sub-concepts, counter-matching the plurality of mined content associated with each second concept. The method may also include providing alternative content to the information streams based on the counter-matched plurality of mined content.

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for identifying pathways in a graph of interconnected nodes. A time series of graph data is captured, which corresponds to events occurring at different nodes in the graph. The graph is traversed to identify consistent and variable pathways, respectively, within the graph. The identified pathways are scored according to a particular feature to establish an expected variance model for the events contained within the graph. Newly received data are compared against the expected variance model to determine a degree to which the newly received data deviates from the expected variance. The variance model is adjusted based on the newly encountered data.

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for identifying pathways in a graph of interconnected nodes. A time series of graph data is captured, which corresponds to events occurring at different nodes in the graph. The graph is traversed to identify consistent and variable pathways, respectively, within the graph. The identified pathways are scored according to a particular feature to establish an expected variance model for the events contained within the graph. Newly received data are compared against the expected variance model to determine a degree to which the newly received data deviates from the expected variance. The variance model is adjusted based on the newly encountered data.

Abstract: An approach is provided for providing spatio-temporal key performance indicators (ST-KPIs). The approach tracks metrics, such as crowd density, pertaining to a number of locations. The tracking is performed over time to develop a history of past values that correspond to the metrics. The history is used to predict a trend of future metrics at the locations with the trend resulting in predicted future values that correspond to the metrics at the locations. In this manner, the ST-KPIs reflect the predicted future values at the various locations that are being monitored. A city view is displayed to a user showing the current and predicted values at defined ST-KPI locations throughout the city.

Abstract: An approach is provided for providing spatio-temporal key performance indicators (ST-KPIs). The approach tracks metrics, such as crowd density, pertaining to a number of locations. The tracking is performed over time to develop a history of past values that correspond to the metrics. The history is used to predict a trend of future metrics at the locations with the trend resulting in predicted future values that correspond to the metrics at the locations. In this manner, the ST-KPIs reflect the predicted future values at the various locations that are being monitored. A city view is displayed to a user showing the current and predicted values at defined ST-KPI locations throughout the city.

Abstract: For distributed analysis of time-series data in a smart entity environment, the data is received from a data source in the environment. An overall analysis of the data is distributed to a first node in the environment. In a network operating the environment the first node is at a smaller distance from the data source as compared to a second node. A first portion of the overall analysis is performed on the data at the first node to produce a first conclusion. The first conclusion is routed to the second node. The second node performs a second portion of the overall analysis. Using the first conclusion, from the first node, a first action is caused to occur on a component of the environment. The data source is associated with the component, the data is indicative of a condition in the environment, and the component participates in the condition.

Abstract: A method for managing user information streams associated with recommendation systems based on cognitively counter-matched mined content is provided. The method may include determining and extracting first concepts from mined content. The method may further include determining second concepts associated with the determined and extracted, wherein the second concepts comprise one or more different interpretations of the first concepts. The method may further include determining relationships between the second concepts by analyzing the second concepts using data mining analysis techniques. The method may further include, based on the determined one or more relationships between the sub-concepts, counter-matching the plurality of mined content associated with each second concept. The method may also include providing alternative content to the information streams based on the counter-matched plurality of mined content.

Abstract: For distributed analysis of time-series data in a smart entity environment, the data is received from a data source in the environment. An overall analysis of the data is distributed to a first node in the environment. In a network operating the environment the first node is at a smaller distance from the data source as compared to a second node. A first portion of the overall analysis is performed on the data at the first node to produce a first conclusion. The first conclusion is routed to the second node. The second node performs a second portion of the overall analysis. Using the first conclusion, from the first node, a first action is caused to occur on a component of the environment. The data source is associated with the component, the data is indicative of a condition in the environment, and the component participates in the condition.

Abstract: A system for facilitating sale of venue event tickets involves: a venue interface; a venue offering database containing records of: currently available tickets, past event ticket acceptances, and acceptance history data; a subscriber database containing, for individual subscribers, at least an identification, interests, and contact information; a pricing module which will identify at least one subscriber to whom ticket(s) should be offered, on an urgent basis, at a reduced price determined using an algorithm taking into account at least: subscriber location, time until start for the event, estimated travel time between subscriber location and venue, and content of the acceptance history data; a communications module which will proactively communicate urgent offers to specific subscribers identified by the pricing module; and an evaluation and learning module which employs unsupervised machine learning to analyze acceptance history data and modify the algorithm used by the pricing module.

Abstract: A system and method is provided for remote active window sensing of a display in a computing device and reporting of the same. The system includes a tool including a remote monitoring and reporting component configured to monitor active windows of one or more remote devices and provide a report to a presenter as to whether the active windows of the one or more remote devices are for a presentation of the presenter.

Abstract: For distributed analysis of time-series data in a smart entity environment, the data is received from a data source in the environment. An overall analysis of the data is distributed to a first node in the environment. In a network operating the environment the first node is at a smaller distance from the data source as compared to a second node. A first portion of the overall analysis is performed on the data at the first node to produce a first conclusion. The first conclusion is routed to the second node. The second node performs a second portion of the overall analysis. Using the first conclusion, from the first node, a first action is caused to occur on a component of the environment. The data source is associated with the component, the data is indicative of a condition in the environment, and the component participates in the condition.

Abstract: For distributed analysis of time-series data in a smart entity environment, the data is received from a data source in the environment. An overall analysis of the data is distributed to a first node in the environment. In a network operating the environment the first node is at a smaller distance from the data source as compared to a second node. A first portion of the overall analysis is performed on the data at the first node to produce a first conclusion. The first conclusion is routed to the second node. The second node performs a second portion of the overall analysis. Using the first conclusion, from the first node, a first action is caused to occur on a component of the environment. The data source is associated with the component, the data is indicative of a condition in the environment, and the component participates in the condition.

Abstract: An approach is provided for providing spatio-temporal key performance indicators (ST-KPIs). The approach tracks metrics, such as crowd density, pertaining to a number of locations. The tracking is performed over time to develop a history of past values that correspond to the metrics. The history is used to predict a trend of future metrics at the locations with the trend resulting in predicted future values that correspond to the metrics at the locations. In this manner, the ST-KPIs reflect the predicted future values at the various locations that are being monitored. A city view is displayed to a user showing the current and predicted values at defined ST-KPI locations throughout the city.

Abstract: An approach is provided for providing spatio-temporal key performance indicators (ST-KPIs). The approach tracks metrics, such as crowd density, pertaining to a number of locations. The tracking is performed over time to develop a history of past values that correspond to the metrics. The history is used to predict a trend of future metrics at the locations with the trend resulting in predicted future values that correspond to the metrics at the locations. In this manner, the ST-KPIs reflect the predicted future values at the various locations that are being monitored. A city view is displayed to a user showing the current and predicted values at defined ST-KPI locations throughout the city.

Abstract: A system and method is provided for remote active window sensing of a display in a computing device and reporting of the same. The system includes a tool including a remote monitoring and reporting component configured to monitor active windows of one or more remote devices and provide a report to a presenter as to whether the active windows of the one or more remote devices are for a presentation of the presenter.

Abstract: A system and method is provided for remote active window sensing of a display in a computing device and reporting of the same. The system includes a tool including a remote monitoring and reporting component configured to monitor active windows of one or more remote devices and provide a report to a presenter as to whether the active windows of the one or more remote devices are for a presentation of the presenter.

Abstract: An information technology services management product is provided with a change management component that identifies conflicts based on a wide range of information. When a change on a configuration item is scheduled, the change management component identifies, for example, affected business applications, affected service level agreements, resource availability, change schedule, workflow, resource dependencies, and the like. The change management component warns the user if a conflict is found. The user does not have to consult multiple sources of information and make a manual determination concerning conflicts. The change management component may also suggest a best time to schedule a change request based on the information available. The change management component provides a constrained interface such that the user cannot schedule a change request that violates any of the above requirements. The change management component also applies these requirements when changing an already scheduled change request.

Abstract: A system and method is provided for remote active window sensing of a display in a computing device and reporting of the same. The system includes a tool including a remote monitoring and reporting component configured to monitor active windows of one or more remote devices and provide a report to a presenter as to whether the active windows of the one or more remote devices are for a presentation of the presenter.

Abstract: A system and method is provided for remote active window sensing of a display in a computing device and reporting of the same. The system includes a tool comprising a remote monitoring and reporting component configured to monitor active windows of one or more remote devices and provide a report to a presenter as to whether the active windows of the one or more remote devices are associated with a presentation of the presenter.

Abstract: A load balancing method incorporates temporarily inactive machines as part of the resources capable of executing tasks during heavy process requests periods to alleviate some of the processing load on other computing resources. This method determines which computing resources are available and prioritizes these resources for access by the load balancing process. A snap shot of the resource configuration and made secured along with all data on this system such that no contamination occurs between resident data on that machine and any data placed on that machine as put of the load balancing activities. After a predetermined period of time or a predetermined event, the availability of the temporary resources for load balancing activities ends. At this point, the original configuration and data is restored to the computing resource such that no trace of use of the resource in load balancing activities is detected to the user.