This disclosure relates generally to a system and method to recommend a targeted advertisement to a user. The system is configured to receive and pre-processes a plurality of data from various sources based on a set of predefined business rules. A set of training data is extracted from the pre-processed plurality of data to develop a machine learning model to identify a set of attributes of personality of the user. A neural network is trained to identify at least one classifier to define one or more needs of the user. It would be appreciated that the one or more needs of the user are mapped with the set of attributes of the personality. Finally, the recommendation module of the system recommends at least one advertisement to a media service provider to share the same over OTT to the user.

Techniques are disclosed utilizing cognitive computing to improve commercial communications from vendors to users. A user's financial account(s) and location may be monitored to determine when a user is within a threshold distance of a vendor. If the user is within the threshold distance the methods and systems disclosed may determine which targeted commercial communications to transmit to the user based upon a shopping profile for the user. The shopping profile may include a dataset indicative of the shopping habits of the user.

Examples to determine media impressions using distributed demographic information are disclosed. An example system includes programmable circuitry to log, at a first Internet domain, a first record for a first website visit by a first client device to a website at a second Internet domain, the first record based on a hypertext transfer protocol (HTTP) request, the first record to include a timestamp, a uniform resource locator (URL), and a user identifier, the timestamp to represent a time of the first website visit, the URL corresponding to the website at the second Internet domain, and weight impression data in a report, the impression data associated with the first record and with second records, the second records corresponding to second website visits to the website via second client devices, the weighting of the impression data based on demographic distributions of audience members corresponding to the first and second records.

Methods, systems and media for presenting media content that was advertised on a second screen device using a primary screen device are provided. In some implementations, a method for advertising media content to a user is provided, the method comprising: receiving an advertisement request from a computing device; receiving association information indicating that the computing device is associated with a media presentation device; receiving user account information associated with the user account; in response to the advertisement request, selecting an advertisement for media content based at least in part on the association information and the user account information; determining whether an indicator of subscription status of the user account to a service is to be presented in connection with the selected advertisement; causing the advertisement to be presented by computing device, wherein the advertisement is associated with instructions that, in response to interaction with the advertisement, cause the computing device to instruct the media presentation device to present the media content and the indicator of subscription status; receiving input indicating that the indicator of subscription status has been selected; causing an application associated with the service to be transmitted to the computing device; and updating the subscription status of the user account in connection with the service.

Some embodiments described herein relate to a computer-implemented method that includes accessing behavioral data, such as web visitation data, of multiple users. A sparse behavioral vector can be defined for each user based on the behavioral data. Each element of each sparse behavioral vector can represent a different potential detectable behavior such that each sparse behavioral vector encodes the behavioral data for that user. Multiple supervised learning models to each sparse behavioral vector to densify the vectors, defining multiple dense behavioral vectors. An unsupervised machine learning technique can be applied to the dense behavioral vectors to cluster, or define subpopulations, based on similarities between the dense behavioral vectors. Delivery of targeted content to a user can be facilitated based on a dense behavioral vector associated with that user being associated with one or more of the clusters or subpopulations.

In general, embodiments of the present invention provide systems, methods and computer readable media for recommending contextually relevant promotions to consumers in order to facilitate their discovery of promotions that they are likely to purchase from a promotion and marketing service.

Data characterizing wireless emissions of a mobile device of a fuel dispenser user can be received. An identity-less parameter associated with the mobile device of the fuel dispenser user can be determined from the received data. A determination of whether the identity-less parameter is associated with a database record characterizing a profile and stored in a profile database can be made. The determination of whether the identity-less parameter is associated with the database record can be provided.

A rule-based reasoning system may receive first transaction-level data for a first transaction that indicates a first transaction amount of the first transaction and a first merchant associated with the first transaction. The system may determine first item-level data for the first transaction that indicates one or more line items associated with the first transaction. The system may infer second item-level data for a second transaction based on the first item-level data and based on: a determination that a second merchant, associated with the second transaction, matches the first merchant associated with the first transaction, and a determination that a second transaction amount, associated with the second transaction, matches the first transaction amount or satisfies a condition that is based on a calculation performed using the first transaction amount and the second transaction amount. The system may output an indication of the second item-level data associated with the second transaction.

A system and method for providing online customized advertisements, and more specifically, A system and method for providing content-aware ad insertion into streaming data using a web server. The web server has a memory having instructions stored thereon, and a processor configured to execute the instructions on the memory to cause the web server to perform operations. The web server transmit streaming data from the content creator computer to the web server, parse the streaming data to identify keywords within the streaming data, when the identified keywords are known in a database of keywords associated with available advertisements, select the available advertisements corresponding to the identified keywords, when the identified keywords are unknown in a database of keywords associated with available advertisements, select generic advertisements, insert the selected advertisements into the streaming data, and rebroadcast the modified streaming data to the content consumer computers.

Value sharing for a social network is provided. One or more servers send, to a client device of a first user of the social network, a support me icon in association with a post on the social network, the post having been created by a second user of the social network, the support me icon configured to cause an advertisement to be presented to the first user responsive to selection of the support me icon by the first user. The one or more servers receive, from the client device, an indication that the advertisement was presented to the to the first user. The one or more servers allocate, to the second user, a first portion of value corresponding to the presentation of the advertisement to the first user, thereby compensating the second user for creating the post on the social network.