Abstract:
Systems and methods for distributing shared electronic coupons are provided. According to one aspect, the electronic coupon may include a coupon benefit display region displaying a textual and/or graphical representation of a coupon benefit. The electronic coupon may further include a candidate display region displaying a list of one or more friends of user who are determined to be redeemer candidates from among friends in a social network profile or address book of the user. Each redeemer candidate friend in the list has an associated selector, and selection by the user of a selector corresponding to a friend causes the client device to send a message to a coupon server to instruct the coupon server to send the electronic coupon to a client device of the selected friend. Predictive models generated through machine learning may aid in selecting the user to which coupons are distributed and the redeemer candidates.
Abstract:
Various embodiments are described for systems and methods for managing data. The system may include a device group configured for peer-to-peer communications, the device group including a computing device and one or more peer computing devices. The system includes a cross device application programming interface (API) that is implemented as a device group API client executed on the computing device and each of the peer computing devices. Each device group API client includes a permissions module that is configured to determine whether a request satisfies a device-group-specific permission for access to data stored on any device associated with the device group. Upon authorization of the request, a file storage module is configured to retrieve and output the requested file.
Abstract:
Systems and methods for facilitating purchase transactions through real-time dynamic marketplace sessions are provided. A method may include pooling offers for goods/services to form a pooled offer, and pooling bids to form a pooled bid. The pooled offer and the pooled bid may be matched to form a pooled offer/bid pair. Methods for inducing and using predictive models for successful configuration of properties and participants with machine learning procedures that operate on data about successful and unsuccessful offers may be employed. A real-time dynamic marketplace session may be established between offer agents associated with the pooled offers and bid agents associated with the pooled bids. Upon a successful conclusion to the negotiation, a purchase transaction for the pooled offer/bid pair may be processed.
Abstract:
A long-term personal agent program, executable as network service and/or on one or more user computing devices and related method for identifying opportunities and making recommendations on behalf of one or more users, are disclosed herein. In one example, the personal agent program includes a monitoring engine configured to monitor and interpret a user's activities over time with a plurality of sensing and logging methodologies according to user authorization, the use of statistical methods for learning to understand a user's goals and behavioral patterns from data, and the use of procedures for computing the expected value of information guiding sensing and logging in different contexts. The personal agent further may include a recommendation methodology configured to make suggestions and to take actions on behalf of the user, in the present moment as well as for future times, based on inferences about user goals and opportunities in the world.