At&t Intellectual Property I, L.p.

At&t Mobility Ii LLC

David Patterson

Jeremy Fix

Sheldon Kent Meredith

Juliette Zerick

Edmond J Abrahamian

Concepts and technologies are disclosed herein for providing and/or interacting with a profile verification service. A processor executing a profile verification service can receive a request to verify a user profile associated with a user of a social networking application. The processor can identify a computing device associated with the user profile, obtain location data that relates to the user profile and the computing device, and identify an activity associated with the computing device based upon the location data. The processor can determine if the user profile is accurate based upon the activity identified. If a determination is made that the user profile is accurate, the processor can verify the user profile. If a determination is made that the user profile is not accurate, the processor can update the user profile.

Profile verification service

To provide mobile device coupons and discounts, a mobile device couponing system is provided to generate and send coupons to mobile devices based on a probability that the mobile device is within a defined region. The value of the coupons can be inversely proportional to the probability that the mobile device is within the defined region. The probabilities can be precomputed by calculating the probability that each cell in grid in or around the defined region is in the defined region using a set of standardized location resolutions. When location information is received from the mobile device, the probability that the mobile device is within the defined region can be retrieved based on the closest cell that matches the location indicated in the location information and the standardized location resolution closest to the location resolution indicated by the mobile device.

Mobile coupon discounts and valuation based on probability of a geofence collision

A method and apparatus for identifying a plurality of users of a service of a network service provider as users known to each other are disclosed. For example, the method implemented via a processor obtains location information of a plurality of users of a service of a network service provider, selects a subset of users from the plurality of users that are deemed to be stationary, generates a score for each particular pair of users selected from the subset of users, determines for each particular pair of users, whether the score that is generated is greater than or equal to a threshold, identifies the pair of users as users who know each other, when the score for the particular pair of users is greater than or equal to the threshold, and performs an analysis to provide an offer to the pair of users, wherein the offer is based on the pair of users being identified as users who know each other.

Method and apparatus for identifying users who know each other

Methods, computer-readable media and apparatuses for predicting an amount of network infrastructure needed for a new neighborhood are disclosed. A processor generates a plurality of different user profiles based upon demographic data of existing customers, historical utilization data and historical usage data, determines a demographic of a new neighborhood, correlates one of the plurality of different user profiles to the new neighborhood based upon the demographic of the new neighborhood and predicts the amount of network infrastructure to be deployed in the new neighborhood based upon the one of the plurality of different user profiles that is correlated to the demographic of the new neighborhood.

Apparatus and method for predicting an amount of network infrastructure needed based on demographics

Methods, computer-readable media and devices for calculating fraud scores for pending payment transactions are disclosed. A method includes a processor receiving a request for a fraud score. The request comprises a notification of a pending payment transaction that is associated with a credit card of a user and associated with a first location. The processor then detects a location of a device associated with the user, calculates a fraud score based upon the location of the device and the first location, and sends a response comprising the fraud score that is calculated.

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Los Altos, CA, United States of America

David Patterson