Abstract: A method and associated systems for automatically identifying critical resources in an organization. An organization creates a model of the dependencies between pairs of resource types, wherein that model describes how the organization's projects and services are affected when a resource type becomes unavailable. This model may include a system of directed graphs. This model may be used to automatically identify a resource type as critical if unacceptable cost is incurred by resuming projects and services rendered infeasible when the resource type is disrupted. The model may also be used to automatically identify a first resource type as critical for a second resource type when disruption of the first resource type forces the available capacity of the second resource type to fall below a threshold value.

Abstract: A method and associated systems for automatically identifying critical resources in an organization. An organization creates a model of the dependencies between pairs of resource types, wherein that model describes how the organization's projects and services are affected when a resource type becomes unavailable. This model may include a system of directed graphs. This model may be used to automatically identify a resource type as critical if unacceptable cost is incurred by resuming projects and services rendered infeasible when the resource type is disrupted. The model may also be used to automatically identify a first resource type as critical for a second resource type when disruption of the first resource type forces the available capacity of the second resource type to fall below a threshold value.

Abstract: Methods and arrangements for measuring and utilizing media topic influence. A publically disseminated media transmission is received. Public influence of the media transmission is measured via: identifying one or more media sources used to disseminate the media transmission; and obtaining one or more predetermined influence values associated with the one or more media sources.

Abstract: A method, system and computer program product are disclosed for candidate screening. In one embodiment, the method comprises identifying a multitude of dimensions of a specified job, assigning a weight to each of the dimensions, and determining whether each of a group of candidate satisfies the weights assigned to the dimensions. In an embodiment, a score is assigned to each candidate based on the weights assigned to the dimensions, and the number of the candidates score above a threshold is determined. In an embodiment, if the number of the candidates that have a score above the threshold is less than a defined number, one or more of the weights is adjusted, and the candidates are rescored based on these adjusted weights. In embodiments of the invention, the weights are adjusted based on the number of the candidates that score above the threshold, or based on the other weights.

Abstract: A method and associated systems for automatically identifying critical resources in an organization. An organization creates a model of the dependencies between pairs of resource instances, wherein that model describes how the organization's projects and services are affected when a resource instance becomes unavailable. This model may be represented as a system of directed graphs. This model may be used to automatically identify a resource instance as “critical” when excessive cost is required to resume all projects and services rendered infeasible by the disruption of that resource instance. This model may also be used to automatically identify a resource instance as “critical for a resource type” when disruption of the resource instance forces the capacity of the resource type available to the entire organization to fall below a threshold value.

Abstract: A description of a resource associated with a service of an entity can be captured. The service can be associated with one or more resources, a constraint, and a demand. The resource can be associated with one or more characteristics including a utility, a limited availability, and a consumption rate. The entity can be an organization or a system. An initial allocation problem associated with the resource can be formulated as a two phase problem. The first phase can be an optimization problem and the second phase can be a restricted allocation problem. The initial allocation problem can be associated with reconfiguring a previously established allocation of a baseline scenario. The optimization problem can be solved optimally or approximately to establish a favorable allocation. The favorable allocation can minimizes the reconfiguration cost of the reconfiguring. The baseline scenario can be a normal operation of the service.

Abstract: To predict edges in a non-cumulative graph, based on a sequence of non-cumulative previous occurrences of the graph, the sequence of non-cumulative previous occurrences of the graph is obtained, and topological properties of each of the previous occurrences of the graph are extracted. Topological similarities between each of the previous occurrences of the graph are computed based on the topological properties. The edges of the graph are predicted by computing a score for each possible edge of the graph, based upon the topological similarities.

Abstract: Techniques for scheduling one or more services are provided. The techniques include obtaining customer information, obtaining one or more service characteristics for each of the one or more services, and using the customer information and the one or more service characteristics to schedule the one or more services.

Abstract: Methods and arrangements for generating process recommendations. Customer information is assimilated, the customer information including a number of present customers. An efficiency matrix is assimilated, which indicates efficiency for each of a plurality of actual resources with respect to each of a plurality of services. At least one hypothetical resource is created, which incorporates a best efficiency from among the actual resources with respect to each of the plurality of services, and a scheduling policy is assimilated. A customer queue is generated with respect to each hypothetical resource and in accordance with the at least one scheduling policy. Each hypothetical resource is mapped to each actual resource and a minimum parameter increase from among pairs comprising a hypothetical resource and an actual resource is determined.

Abstract: A data validation service includes providing a user interface to a subscriber of the service via a computer device of the subscriber, receiving a data validation rule specified by the subscriber and an address of a database subject to the data validation, and generating a configuration file that includes the address of the database. The service also includes transmitting the configuration file and a thin client application to the computer device over a network, the thin client application configured to read the configuration file and pull data from the database. The service further includes receiving the data from the computer device via the network, performing the data validation by executing the data validation rule with respect to the data, and compiling results of the data validation and providing the results to the computer device.

Abstract: A data validation service includes providing a user interface to a subscriber of the service via a computer device of the subscriber, receiving, via the user interface, a data validation rule specified by the subscriber and an address of a database subject to the data validation, and generating a configuration file that includes the address of the database and an address of a location of executable code corresponding to the data validation rule. The data validation service also includes transmitting the configuration file and remote methods to the computer device over the network. The remote methods are configured to execute the data validation rule with respect to the data and compile results of the execution.

Abstract: A method, system and computer program product are disclosed for modeling the temporal behavior of clients to develop a predictive system to influence client relationships. In an embodiment, the method comprises establishing for each of a plurality of clients a temporal model for a given time period, and the temporal model identifies a plurality of factors as contributing to a specified relationship with the each client over the given time period. For each of a plurality of different stages of the given time period, the temporal model identifies one or more of these factors as contributing to the specified relationship with the each client. One of the clients is identified as a model client for another client, and the temporal model of this model client is used to predict one or more of the plurality of factors as contributing to a specified relationship with this another client at a specified time.

Abstract: A plurality of application profiles are obtained, for a plurality of applications. Each of the profiles specifies a list of resources, and requirements for each of the resources, associated with a corresponding one of the applications. Specification of a plurality of constraints associated with the applications is facilitated, as is obtaining a plurality of cost models associated with at least two different kinds of servers on which the applications are to run. A recommended server configuration is generated for running the applications, by formulating and solving a bin packing problem. Each of the at least two different kinds of servers is treated as a bin of a different size, based on its capacity, and has an acquisition cost associated therewith. The size is substantially equal to a corresponding one of the resource requirement as given by a corresponding one of the application profiles. Each of the applications is treated as an item, with an associated size, to be packed into the bins.

Abstract: To predict edges in a non-cumulative graph, based on a sequence of non-cumulative previous occurrences of the graph, the sequence of non-cumulative previous occurrences of the graph is obtained, and topological properties of each of the previous occurrences of the graph are extracted. Topological similarities between each of the previous occurrences of the graph are computed based on the topological properties. The edges of the graph are predicted by computing a score for each possible edge of the graph, based upon the topological similarities.

Abstract: Methods and arrangements for prioritizing customer service restoration, in the event of service failure or compromise such that any adverse effect of the service disruption on the customer is minimized, the perceived drop in quality of service, if any, is minimized and timely and efficient resource reallocation for service restoration is achieved. Input data relating to customer service protocols is assimilated. A service restoration order is implemented responsive to a service disruption and based on the assimilated input data. This implementing includes determining bufferable and non-bufferable services, postponing restoration of the bufferable services, and determining an order of priority of the non-bufferable services.

Abstract: A plurality of application profiles are obtained, for a plurality of applications. Each of the profiles specifies a list of resources, and requirements for each of the resources, associated with a corresponding one of the applications. Specification of a plurality of constraints associated with the applications is facilitated, as is obtaining a plurality of cost models associated with at least two different kinds of servers on which the applications are to run. A recommended server configuration is generated for running the applications, by formulating and solving a bin packing problem. Each of the at least two different kinds of servers is treated as a bin of a different size, based on its capacity, and has an acquisition cost associated therewith. The size is substantially equal to a corresponding one of the resource requirement as given by a corresponding one of the application profiles. Each of the applications is treated as an item, with an associated size, to be packed into the bins.

Abstract: A plurality of application profiles are obtained, for a plurality of applications. Each of the profiles specifies a list of resources, and requirements for each of the resources, associated with a corresponding one of the applications. Specification of a plurality of constraints associated with the applications is facilitated, as is obtaining a plurality of cost models associated with at least two different kinds of servers on which the applications are to run. A recommended server configuration is generated for running the applications, by formulating and solving a bin packing problem. Each of the at least two different kinds of servers is treated as a bin of a different size, based on its capacity, and has an acquisition cost associated therewith. The size is substantially equal to a corresponding one of the resource requirement as given by a corresponding one of the application profiles. Each of the applications is treated as an item, with an associated size, to be packed into the bins.

Abstract: At least a first future external event is obtained as input. At least one future effect of the at least one future external event is predicted. The at least first future external event is similar to at least a first past external event. Future utilization of at least one tangible resource is forecast by superimposing events-normalized forecasted data and the at least one predicted future effect of the at least one future event similar to the at least first past external event.

Abstract: Techniques for scheduling one or more services are provided. The techniques include obtaining customer information, obtaining one or more service characteristics for each of the one or more services, and using the customer information and the one or more service characteristics to schedule the one or more services.

Abstract: A plurality of application profiles are obtained, for a plurality of applications. Each of the profiles specifies a list of resources, and requirements for each of the resources, associated with a corresponding one of the applications. Specification of a plurality of constraints associated with the applications is facilitated, as is obtaining a plurality of cost models associated with at least two different kinds of servers on which the applications are to run. A recommended server configuration is generated for running the applications, by formulating and solving a bin packing problem. Each of the at least two different kinds of servers is treated as a bin of a different size, based on its capacity, and has an acquisition cost associated therewith. The size is substantially equal to a corresponding one of the resource requirement as given by a corresponding one of the application profiles. Each of the applications is treated as an item, with an associated size, to be packed into the bins.