Methods and systems for performing an advertisement based single step electronic transaction with or without using a custom application are provided. According to one aspect, a method for performing an advertisement based single step electronic transaction comprises, at a backend server: receiving an indication that a user is interested in a product in an advertisement that was presented to the user; generating transaction information, the transaction information including product information, payment instrument information, and shipping information, and presenting it to the user in a manner such that the user need only perform a single step in order to trigger the transaction; detecting that the user has performed the single step; initiating the transaction; and notifying the user of the result of the transaction.

A system for integrating custom benefits into a communication transmission exchange is provided. The communication transmission exchange may include a plurality of entities. The system may include a receiver configured to receive a custom benefit selection. A second entity may perform the selection. The custom benefit may be associated with a first entity. The selection may trigger termination of any predetermined benefits to be communicated from a fourth entity to the second entity. The predetermined benefits may have been previously associated with a communication associated with the custom benefit. The selection may trigger instantiation of a communication line between the first entity and the second entity. The communication line may be for delivering a custom benefit communication, associated with the custom benefit, from the first entity to the second entity. The selection may also trigger deliverance of the custom benefit communication from the first entity to the second entity.

Systems, methods, and computer-readable media for generating group-based sequential point-of-interest (POI) recommendations are disclosed. A primitive graph or sparse transition matrix is constructed that represents relationships between users, between POIs, and between users and POIs. A loss data prediction algorithm is executed on the primitive graph to obtain a filled graph, which may be a filled user-POI bipartite graph. A group sequential recommendation engine then performs an iterative sequential recommendation process that involves performing, at each iteration, various manipulations on the filled graph to obtain first a homogenous node type graph and then a minimum spanning tree. A next POI to recommend in a sequence of POIs is then determined from the minimum spanning tree. The iterative process continues until stopping criteria is met.

The disclosure relates to securing and enabling user control of profiling data, blockchain-driven matching of users and advertiser-identified anonymous profiling data records of interest, and smart contracts encoded by blockchain for executing transactions. The system may include an anonymized database of profiling data, which is unlinked to any user. The system may implement a private blockchain to store user-defined settings that provide user control over whether and how the profiling data may be used. If a grant to use the data is received, a link is stored that allows the system to identify a user associated with the anonymous profiling data records. If the grant is revoked, the link may be removed. The system may also implement public blockchain technology to record a public information relating to grants, online marketing transactions, making them verifiable, immutable, and transparent for various stakeholders including advertisers, publishers, and users.

A system and method having an improved communication system and method to permanently create and maintain private connections between entities such as two people, businesses, and/or other types of organizations and entities whereby to create an account with the example communication system, a user may complete an online personal contact application, such that once the information is verified, the user may be assigned a Unique Identification.

A computer system operates to detect a series of activities performed by a user, where the activities include interactions as between the user and one or more user interface components. The computer system recognizes the of activities as a sequence of events, where each event of the sequence corresponds to one more activities of the series. In response to the computer system detecting a current user activity, the computer system determines at least one of a user intent or interest based on an analysis of a relevant portion of the sequence of events.

Approaches provide for or automatically optimizing sponsored content campaigns for a sponsored content provider for a particular consumption category across different content publisher networks. For example, performance data for sponsored content campaigns can be used to train a model for a consumption category to determine allocation scores that quantify a relationship between target audiences and the consumption category. In response to a content placement request to initiate a sponsored content campaign associated with the consumption category, allocation scores can be determined and used to dynamically determine an allocation of resources to appropriate audiences or segments based at least in part upon the trained optimization model. A campaign template can be generated that includes the target audience(s), sponsored content, and respective budget allocation, and any other information for the campaign. The campaign can proceed based at least in part on the campaign template, and performance of the campaign can be monitored and analyzed during the campaign to optimize the campaign dynamically.

A system for providing non-repudiation and data integrity of communications online is shown and described. The system has one or more servers communicably connected to a communications network, the one or more server including at least one processor configured for receiving, from a first party, an ad request for an ad impression available for sale. The ad request includes a plurality of attributes associated with the ad impression and a first cryptographic proof that provides non-repudiation and data integrity of the ad request, wherein the first cryptographic proof comprises a second cryptographic proof of the first party; and, authenticating non-repudiation and data integrity of the ad request by querying a blockchain having a public key infrastructure. The public key infrastructure also has a public key associated with the first party. Furthermore, the public key infrastructure authenticates the second cryptographic proof against the public key associated with the first party.

Described are systems and methods for dynamically generating advertisements for presentation in an application executing on a client device, such as an application executing on a smart phone or tablet of a user. The described systems and methods select content items of specific content types based on determined user preference for content types as well as the device capabilities and access permissions of the application through which the advertisement is to be presented.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for personalizing offers are provided. One of the methods includes: collecting response data comprising one or more offers made to each of a plurality of users of a platform and one or more corresponding responses, wherein the one or more offers are from a group of offer choices; creating a training dataset comprising the collected response data and one or more features associated with each of the plurality of users; training a machine learning model using the training dataset, wherein the trained machine learning model is configured to predict the plurality of users' responses to future offers; obtaining a plurality of projected profits for the platform using the trained machine learning model, wherein each of the plurality of projected profits corresponds to making one of the group of the predetermined offers to one of the plurality of users.