Abstract: An aspect of the disclosure includes a method, a system and a computer program product for retargeting content to a decision making unit. The method including determining a journey stage for each of the plurality of individuals. A retargeting strategy is identified for each of the plurality of individuals, the retargeting strategy based at least in part on the journey stage for each of the plurality of individuals and a cost factor. Content data is transmitted to at least one of the plurality of individuals using retargeting based at least in part on the retargeting strategy.

Abstract: Identifying one or more patterns of content consumption across multiple entities and determining an engagement action for a user of an entity based on the patterns may include receiving information associated with content, cross-industry user data associated with consumption of the content, and a given organization user data associated with consumption of the content. A first set of consumption profile vectors associated with the given organization and one or more second set of consumption profile vectors associated respectively with one or more cross-industry organizations may be generated. Information associated with a target user in the given organization may be received. A customized learning plan for the target user in the given organization may be generated based on the first set of consumption profile vectors, the one or more second set of consumption profile vectors, and the information associated with the target user.

Abstract: A computer readable medium embodies a program of machine-readable instructions executable by a processing apparatus to perform operations including determining information corresponding to a number of differences in distances between ending points of journeys taken by a vehicle and starting points of consecutive journeys taken by the vehicle, and transmitting one or more representations of the information. Another computer readable medium tangibly includes instructions for, for each of a number of vehicles, receiving one or more scores corresponding to a vehicle, and determining a ranked list containing at least a portion of the scores, and outputting the ranked list. Another computer readable medium includes instructions for, for each of a number of vehicles, receiving information corresponding to a vehicle, using one or more metrics, calculating one or more values from the received information, and communicating one or more representations of the one or more value to one or more entities.

Abstract: Enterprise learning system may receive as input learning goals for a learner. Learning goals may also be specified by job-roles. The system may output course-sequence recommendations, sequence-associations to learning goals and learning-goal recommendations. A semantic analysis may automatically relate learning-goals to learning assets and job-roles. Computational semantic relation-finding may leverage available knowledge-bases. A sequence-recommendation recommends course or learning asset sequences to the learner based on historical usage, the learner's current and/or desired job-roles and learning goals.

Abstract: A mechanism is provided for generating a set of color palettes for a product to be marketed. Color-related information of each image in a set of images is extracted. Using a user provided targeted product, targeted brand, and targeted brand message(s) to be marketed, computational logic is applied to generate a set of new color palettes for use in product design or product packaging design. The set of new color palettes is presented to the user. Responsive to the user selecting a color palette from the set of new color palettes, a color analysis of the selected color palette is performed. The results of the color analysis are then presented to the user.

Abstract: A mechanism is provided for generating a set of color palettes for a product to be marketed. Color-related information of each image in a set of images is extracted. Using a user provided targeted product, targeted brand, and targeted brand message(s) to be marketed, computational logic is applied to generate a set of new color palettes for use in product design or product packaging design. The set of new color palettes is presented to the user. Responsive to the user selecting a color palette from the set of new color palettes, a color analysis of the selected color palette is performed. The results of the color analysis are then presented to the user.

Abstract: Evaluating aesthetics of image data is disclosed. Evaluating aesthetics of image data can include identifying a first set of aesthetics data from a first set of image data. Evaluating aesthetics of image data can include generating an aesthetics evaluation score for the first set of image data, the aesthetics evaluation score generated based on the first set of aesthetics data and a first set of aesthetics data rules. Evaluating aesthetics of image data can include determining that the aesthetics evaluation score achieves an aesthetics threshold. Evaluating aesthetics of image data can include endorsing the first set of image data in response to determining that the aesthetics evaluation score achieves the aesthetics threshold.

Abstract: A computing device identifies one or more contextual variables within one or more social media messages. The computing device determines a contextual influence value based on the one or more social media messages. The computing device determines an appetite level. The computing device determines an unadjusted expected value of pleasantness based on the determined contextual influence value and the determined appetite level.

Abstract: A computer readable medium embodies a program of machine-readable instructions executable by a processing apparatus to perform operations including determining information corresponding to a number of differences in distances between ending points of journeys taken by a vehicle and starting points of consecutive journeys taken by the vehicle, and transmitting one or more representations of the information. Another computer readable medium tangibly includes instructions for, for each of a number of vehicles, receiving one or more scores corresponding to a vehicle, and determining a ranked list containing at least a portion of the scores, and outputting the ranked list. Another computer readable medium includes instructions for, for each of a number of vehicles, receiving information corresponding to a vehicle, using one or more metrics, calculating one or more values from the received information, and communicating one or more representations of the one or more value to one or more entities.

Abstract: Selecting candidates from a set of candidates by receiving a set of input parameters about a single aspect of the candidates and applying multiple scoring methods to those input parameters to compute a candidate score via each scoring method. A subset of zero or more candidates is then selected from the set of candidates by applying one or more selection criteria to the set of scores. There is not necessarily a value for every input parameter of every candidate.

Abstract: Techniques for providing a reservation system are provided. The techniques include displaying a scalable visualization object, wherein the scalable visualization object comprises an expanded view element of the reservation system depicting information in connection with a selected interval of time and a compressed view element of the reservation system depicting information in connection with one or more additional intervals of time, maintaining a visual context between the expanded view and the compressed view within the visualization object, and enabling a user to switch between the expanded view and the compressed view to facilitate use of the reservation system.

Abstract: A tool for computational generation of organizational mentoring relationships. The tool determines a mentor pool and a mentee pool based, at least in part, on per-person domain metric data for each person in a general pool. The tool determines a plurality of per-metric ranked mentor lists for each of the one or more mentees in the mentee pool. The tool determines a per-mentee fused rank list for each of the one or more mentees in the mentee pool. The tool determines, based, at least in part, on the per-mentee fused rank list for each of the one or more mentees in the mentee pool, one or more cross-organizational mentorship assignments. The tool establishes, based, at least in part, on the one or more cross-organizational mentorship assignments, at least one mentor-mentee relationship for each of the one or more mentees in the mentee pool.

Abstract: A computer readable medium embodies a program of machine-readable instructions executable by a processing apparatus to perform operations including determining information corresponding to a number of differences in distances between ending points of journeys taken by a vehicle and starting points of consecutive journeys taken by the vehicle, and transmitting one or more representations of the information. Another computer readable medium tangibly includes instructions for, for each of a number of vehicles, receiving one or more scores corresponding to a vehicle, and determining a ranked list containing at least a portion of the scores, and outputting the ranked list. Another computer readable medium includes instructions for, for each of a number of vehicles, receiving information corresponding to a vehicle, using one or more metrics, calculating one or more values from the received information, and communicating one or more representations of the one or more value to one or more entities.

Abstract: A system and method for scheduling resources includes a memory storage device having a resource data structure stored therein which is configured to store a collection of available resources, time slots for employing the resources, dependencies between the available resources and social map information. A processing system is configured to set up a communication channel between users, between a resource owner and a user or between resource owners to schedule users in the time slots for the available resources. The processing system employs social mapping information of the users or owners to assist in filtering the users and owners and initiating negotiations for the available resources.

Abstract: A system and method for scheduling resources includes a memory storage device having a resource data structure stored therein which is configured to store a collection of available resources, time slots for employing the resources, dependencies between the available resources and social map information. A processing system is configured to set up a communication channel between users, between a resource owner and a user or between resource owners to schedule users in the time slots for the available resources. The processing system employs social mapping information of the users or owners to assist in filtering the users and owners and initiating negotiations for the available resources.

Abstract: A method of implementing a bargaining strategy includes receiving a first plurality of attributes corresponding to team members of a first team, and a second plurality of attributes corresponding to team members of a second team. The two teams participate in a bargaining process and each team bargains pursuant to a majority rule. The method includes determining at least one critical first team member from the first team using the first plurality of attributes, and at least one critical second team member from the second team using the second plurality of attributes. The at least one critical first and second team members are determinative of an agreeable outcome of the bargaining process. The method includes generating suggested bargaining terms likely to result in the agreeable outcome of the bargaining process between the first and second teams according to the at least one critical first and second team members.

Abstract: A method of implementing a bargaining strategy includes receiving a first plurality of attributes corresponding to team members of a first team, and a second plurality of attributes corresponding to team members of a second team. The two teams participate in a bargaining process and each team bargains pursuant to a majority rule. The method includes determining at least one critical first team member from the first team using the first plurality of attributes, and at least one critical second team member from the second team using the second plurality of attributes. The at least one critical first and second team members are determinative of an agreeable outcome of the bargaining process. The method includes generating suggested bargaining terms likely to result in the agreeable outcome of the bargaining process between the first and second teams according to the at least one critical first and second team members.

Abstract: A method includes obtaining transaction data for two or more items, determining valuations for the two or more items, grouping the two or more items into one or more bundles, wherein each bundle comprises a different combination of the two or more items, estimating a joint distribution of valuations for the two or more items in each of the one or more bundles based on the transaction data for the two or more items, and estimating expected profits for each of the one or more bundles over a range of bundle prices from the joint distribution.

Abstract: A method for systematically determining a pricing strategy based on one or more of a business insight, a price perception model and a surprise model.

Abstract: A method for estimating a risk associated with a project includes preparing a plurality of data models, where each of the plurality of data models examines a different dimension of the project, classifying each of the plurality of data models to produce a plurality of prediction models, where each of the plurality of prediction models is defined by a plurality of quality metrics, and where the plurality of quality metrics includes a preliminary estimate of the risk and a measure of confidence in the preliminary estimate, and computing a refined estimate of the risk based on a quality of the plurality of quality metrics.