Abstract: A system, method and computer program product for determining a target population to be subject to a promotion or offer of goods/services. The target population is determined that strongly prefers a given promotion, while also making sure the target population represents a sizable number of consumers such that profits may be maximized. The system provides an output solution listing available promotion options and one or more corresponding target groups based on solving an optimization problem that incorporates, prior obtained most important customer features for each promotion using historical promotion data and statistics measures. The system may automatically initiate a promotion offering to each of said customers by communicating the promotion to the members of the targeted group of people, wherein a percentage of future transactions to which the promotion is offered is expected to exceed a threshold level.

Abstract: A hardware processor coupled to a transaction data database and a customer data database receives transaction data and customer data, and executes a predictive modeling algorithm that determines customer features that characterize purchasing behavior from the customer data and the transaction data. The hardware processor executes a clustering algorithm that segments customers into multiple groups based on the customer features. A likelihood function is constructed based on a selected demand model, the transaction data and customer segment information determined from the multiple groups, the likelihood function determined based on probability that each sales transaction belongs to a segment conditioned on a paid price. A model estimator computes parameters that maximize the likelihood function.

Abstract: A system, method and computer program product for determining a target population to be subject to a promotion or offer of goods/services. The target population is determined that strongly prefers a given promotion, while also making sure the target population represents a sizable number of consumers such that profits may be maximized. The system provides an output solution listing available promotion options and one or more corresponding target groups based on solving an optimization problem that incorporates, prior obtained most important customer features for each promotion using historical promotion data and statistics measures. The system may automatically initiate a promotion offering to each of said customers by communicating the promotion to the members of the targeted group of people, wherein a percentage of future transactions to which the promotion is offered is expected to exceed a threshold level.

Abstract: Training a machine to learn to offer personalized promotions over a network is provided. A promotion optimization engine may take logit models and their confidence measures, and compute the acceptance probability of each promotion based on the customer and product features. A target promotion may be determined based on an objective function, which jointly considers the acceptance probability and the logit model's confidence level. A cognitive engine receives a user response to the promotion and based on the user response, updates parameters of the logit model and confidence level associated with the logit model. In one aspect, a signal to offer the promotion is transmitted via a communication channel to a user's device, wherein the signal causes the user's device to automatically connect to one or more of the processors to receive the promotion, e.g., when the user's device is online.

Abstract: A computer-based system provides identification and determination of possible fraud/risk in procurement. Both transactional data and social media data are analyzed to identify fraud and discover potentially colluding parties. A comprehensive solution incorporates text analytics, business/procurement rules, and social network analysis. Furthermore, both unsupervised and supervised machine learning can provide improved accuracy over time as more data is captured and analyzed and updates repeated. The system can include modular or integrated components, allowing for certain customized or commercially available components to be utilized in accordance with the comprehensive solution.

Abstract: The present invention provides a method, system and computer program product for implementing an automated inventory replenishment process between a manufacturer and a business partner. In one embodiment of the invention, a method is provided comprising the business partner purchasing and maintaining an inventory of goods from the manufacturer, and the manufacturer providing price protection to the business partner for the purchasing of the goods. This embodiment further comprises managing said inventory by using an automated process that takes into account said price protection for the purchasing of the goods.

Abstract: The present invention provides a method, system and computer program product for implementing an automated inventory replenishment process between a manufacturer and a business partner. In one embodiment of the invention, a method is provided comprising the business partner purchasing and maintaining an inventory of goods from the manufacturer, and the manufacturer providing price protection to the business partner for the purchasing of the goods. This embodiment further comprises managing said inventory by using an automated process that takes into account said price protection for the purchasing of the goods.

Abstract: The present invention provides a method, system and computer program product for implementing an automated inventory replenishment process between a manufacturer and a business partner. In one embodiment of the invention, a method is provided comprising the business partner purchasing and maintaining an inventory of goods from the manufacturer, and the manufacturer providing price protection to the business partner for the purchasing of the goods. This embodiment further comprises managing said inventory by using an automated process that takes into account said price protection for the purchasing of the goods.

Abstract: A computer-implementable method, system and computer media for allocating and managing insignificant areas of Graphical User Interface (GUI) real estate are presented. In a preferred embodiment, the computer-implementable method includes identifying an insignificant area of GUI real estate in a GUI that is used by a first application. The identified insignificant area of GUI real estate is then populated with a graphical element of a second application.