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 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 user trajectory graph may be constructed based on spatio-temporal data. A mobility pattern may be extracted from the user trajectory graph. Users may be clustered into groups, wherein the users in a same group possess similar feature values in the mobility pattern, and the users in different groups have different feature values, to identify personas and location sets. A distribution model may be constructed that models user timing and location preference, wherein an outcome indicates a preference for a particular time bin on a particular day for a particular location.
Abstract:
A system, method and program product for bundling resources for a resource provisioning platform. A system is disclosed that includes a plurality of resources, wherein each resource belongs to one of a plurality of categories; a bundling system having: a data collection system that gathers historical transaction data associated with the resources; an analysis system that analyzes the historical transaction data to assign estimated valuations to different bundles of resources and includes (a) a substitution effect analyzer to analyze a substitution effect of resources in each category using discrete choice modeling and marginal value estimation, and (b) a joint dependence analyzer that determines intra-category and inter-category joint dependent inferences across all resources; and a bundle selection system that selects a set of bundles for provisioning based on the estimated valuations.
Abstract:
A method and system are provided. The method includes converting, by a computer having a processor and a memory, categorical sequence data for a customer journey into a numerical similarity matrix. The method further includes learning, by the computer, features of the customer journey by applying a distance metric learning based matrix factorization approach to the numerical similarity matrix.
Abstract:
A method and system are provided. The method includes receiving by a computer having a processor and a memory, sequence data that includes labeled data and unlabeled data. The method further includes generating, by the computer having the processor and the memory, a recurrent neural network model of the sequence data, the recurrent neural network model having a recurrent layer and an aggregate layer. The recurrent neural network model feeds sequences generated from the recurrent layer into the aggregate layer for aggregation, stores temporal dependencies in the sequence data, and generates labels for at least some of the unlabeled data.
Abstract:
Methods and a system are provided that is performed by a computer server for inferring location context categories for a set of mobile users having at least two members. A method includes, for each mobile user in the set, obtaining at least one location context category therefor from publically available information responsive to uncertain mobile device location data. The method further includes applying multi-user collaborative machine learning to the at least one location context category for each mobile user in the set to infer a single refined location context category for each mobile user in the set.
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 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 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.