Aspects of the subject disclosure may include, for example, storing, in a database, a decorating style preference of a user; receiving, from user equipment of the user, one or more images (and/or one or more 2D environment models and/or one or more 3D environment models) depicting an environment in which remodeling is desired; generating, via a machine learning process, a first model to present by the user equipment, the generating the first model being based upon the decorating style preference and the one or more images (and/or the one or more 2D environment models and/or the one or more 3D environment models), the first model comprising a first remodeling proposal for the environment; sending, to the user equipment, the first model, the sending of the first model facilitating display by the user equipment of a first depiction of the environment as proposed by the first remodeling proposal; receiving, from the user equipment, feedback information regarding the first remodeling proposal; generating, via the machine learning process, a second model to present by the user equipment, the generating the second model being based upon the decorating style preference, the one or more images (and/or the one or more 2D environment models and/or the one or more 3D environment models), and the feedback information, the second model comprising a second remodeling proposal for the environment; and sending, to the user equipment, the second model, the sending of the second model facilitating display by the user equipment of a second depiction of the environment as proposed by the second remodeling proposal. Other embodiments are disclosed.

A delayed grouping (batch) processing of previous campaign delivery pacing decisions and corresponding outcomes (deliveries) is used to configure a new auction experiment iteration. In the new iteration, a campaign that was previously over-delivered is classified as either (a) over-delivered due to incorrect pacing or (b) over-delivered due to auction experiment design. After the delayed processing, the new auction experiment iteration is conducted with a mitigating action taken on the previously over-delivered campaign if the campaign is classified as (b) over-delivered due to auction experiment design. For example, the mitigating action can include removing the campaign from a subsequent iteration of the experiment, or the experiment can be redesigned. By doing so, the over-delivery caused by the campaign due to the auction experiment design is avoided when performing the new auction experiment iteration.

Aspects of the subject disclosure may include, for example, obtaining first data associated with a first presentation of a first portion of a first video, obtaining second data, wherein the second data is obtained: from a creator of the first video, by performing an analysis on the first portion of the first video, or a combination thereof, identifying an emotional trajectory of a first user during the first presentation in accordance with the first data and the second data, selecting a first creative in accordance with the emotional trajectory, and transmitting the first creative to a first communication device. Other embodiments are disclosed.

A system for training a bidding model comprising: a plurality of tactics stored on at least one database; a plurality of hyperparameters; in response to an available inventory from a publisher relayed through a real time bid server, computing a bid on the available inventory; sending the bid to the real time bid server; receiving an auction result in response to the bid; calculating a plurality of rewards based on the auction result and the tactics; calculate a plurality of q values based on the rewards; calculate a plurality of losses; backpropogating the losses through the bidding model.

A method of managing use of a digital billboard. The method comprises determining, by an analysis application executing on a computer system, a plurality of mobile viewsheds for each of a plurality of mobile communication devices, where a mobile viewshed comprises a location, a speed, a direction of travel of the mobile communication device, accessing demographic and profile information of a subscriber associated with the device, determining an arcscore for each of the mobile viewsheds that intersect a static viewshed of the digital billboard based in part on the speed of the mobile viewshed and the angular alignment of the direction of travel of the mobile viewshed with an orientation of the static viewshed of the digital billboard, and rotating content presentation on the digital billboard at a rate determined in part based on the arcscores and based on the average traffic speed.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for efficiently allocating resources among participants. Methods can include receiving valuation data specifying, for each of a plurality of entities, a respective valuation for each of a plurality of resource subsets, each resource subset comprising a different combination of one or more resources of a plurality of resources. After receiving valuation data, assigning each resource in the plurality of resources to a respective entity of the plurality of entities based on the valuations and generating, for each particular entity, a respective input representation that is derived from valuations of every other entity in the plurality of entities other than the particular entity. The input representation for each particular entity is processed using a neural network to generate a rule for the particular entity and a payment based on the rule output for the entities.

Disclosed is a computer implemented method of bidding for advertisement opportunities based on user behavior data. The computer implemented method may include receiving a primary bid value associated with an audience list including a plurality of users. Further, each user of the plurality of users may be associated with user behavior data corresponding to a primary filtering criteria. Further, the computer implemented method may include receiving a secondary bid value associated with a sub-audience list including one or more users. Further, the one or more users may be associated with user behavior data corresponding to a secondary filtering criteria. Additionally, the computer implemented method may include transmitting a bid for an advertisement opportunity based on each of the primary bid value and the secondary bid value. The advertisement may be presentable to the one or more users.

A media presentation and distribution system (MPDS) that handles rules-based presentation of non-programming media items, receives a user request (which includes user parameters) for delivery of programming media content at a first client device and transmits a media stream that includes the programming media content with a plurality of identifiers present with the programming media content. The MPDS further receives a request that includes one or more user preferences from the first client device, based on a detection of the plurality of identifiers. The MPDS further determines a set of non-programming media items for delivery to the first client device. The MPDS further controls presentation of a part of the media stream on a second client device that is paired with the first client device based on a movement of the second client device in a communication range of the second client device with the first client device.

Aspects of the subject disclosure may include, for example, monitoring a performance of a creative presented by a first plurality of client devices in conjunction with a distribution of a first content item via a first outlet, determining that the performance exceeds a threshold, responsive to the determining that the performance exceeds the threshold, identifying a second outlet to distribute the first content item, and providing the first content item to the second outlet responsive to the identifying of the second outlet. Other embodiments are disclosed.

Aspects of the subject disclosure may include, for example, obtaining a first image, the first image comprising a depiction of a first product of a first potential advertiser; analyzing the first image to determine a first spatial placement of the first product, the first spatial placement being relative to another object in the first image; receiving, from user equipment, a user image that shows a depiction of a user environment; analyzing the user image, the analyzing resulting in a plurality of identified objects; determining whether the another object corresponds to a corresponding one of the plurality of identified objects; responsive to a determination that the another object corresponds to the corresponding one of the plurality of identified objects, generating information that places the depiction of the first product in the depiction of the user environment; and responsive to the generating, transmitting the information to the user equipment. Other embodiments are disclosed.