An online system generates a cluster group and uses membership in the cluster group as an eligibility criteria for presenting a content item. The online system receives a request from a third party system to present the content item. The online system also receives identification information about users who have visited webpages associated with the third party system and descriptive information associated with the webpages. Based on the descriptive information, the online system extracts tags for the webpages and classifies the webpages into one or more categories that include a category associated with the content item. The online system generates a seed group that includes users who visited webpages in the category associated with the content item. The online system further expands the seed group to a cluster group by applying a cluster model to one or more characteristics of each candidate user not included in the seed group.

The present disclosure provides systems and methods for electronically providing each of a plurality of content distributors with access to a library of content items, facilitating the selection of a combination of the content items, creating a unique set of links for each recipient-distributor combination, and distributing the selected content and unique links via one or more distribution channels to a plurality of recipients. As each link is associated with both a recipient and a distributor, conversion actions stemming from the selection of a link by a recipient are attributed to the proper distributor. Distributors can create content distribution approaches that can be shared with other distributors.

Systems, methods, computer-readable media, and apparatuses for identifying and executing one or more interactive condition evaluation tests to generate an output are provided. In some examples, user information may be received by a system and one or more interactive condition evaluation tests may be identified. An instruction may be transmitted to a computing device of a user and executed on the computing device to enable functionality of one or more sensors that may be used in the identified tests. A user interface may be generated including instructions for executing the identified tests. Upon initiating a test, data may be collected from one or more sensors in the computing device. The data collected may be transmitted to the system and may be processed using one or more machine learning datasets to generate an output.

Systems and methods are provided herein for providing recommendations to a user. A short-media viewing profile may be maintained for the user. The short-media viewing profile may be based on user's behavior while watching short-length media content. A long-media viewing profile may be maintained for the user. The long-media viewing profile may be based on user's behavior while watching long-length media content. In response to determining that the user is currently engaged in viewing short-length media content, a recommendation is provided to the user based on the short-media viewing profile. In response to determining that the user is currently engaged in viewing long-length media content, a recommendation is provided to the user based on the long-media viewing profile.

Methods, apparatus, systems, and articles of manufacture are disclosed to extract information from uniform resource locators (URLs). An example system includes at least one memory, programmable circuitry, and instructions to cause the programmable circuitry to collect first uniform resource locator (URL) information from a server of an Internet-based media publisher, the first URL information corresponding to first media accessed by first users, determine first URL components in the first URL information, and determine feature-to-user assignment rules based on the first URL components.

Aspects of the subject disclosure may include, for example, identifying user preferences for an XR application executing at an XR user system, wherein the user preferences are associated with an XR application user, accessing a historical profile associated with the XR application user, receiving local environment information from a sensor array of the XR user system, selecting an XR object for presentation on an XR display of the XR user system based on the local environment information, the user preferences, and the historical profile, and allocating compute resources to facilitate a rendering of the XR object, wherein the allocated compute resources are selected from a compute resource pool comprising local compute resources of the XR user system and edge compute resources of a network. Other embodiments are disclosed.

A press release distribution system provides press release and other news to forum sites as posts. The forum software that runs at forum sites includes press release interface software or is adapted to receive press release interface plug-in modules for interfacing with the press release distribution system. The press release interface software or plug-in module may also monitor and/or analyze user data of forum members and/or forum activities of the users. The monitored user data and forum activities may be provided to the press release distribution system for analysis and generation of user profiles. Using the result of the analysis (e.g., user profiles), the press release distribution system can target particular users or forums to direct the press releases, news, or advertisements for most effective advertising campaign.

Methods and apparatus to deliver targeted advertising are disclosed. An example apparatus includes processor circuitry to: obtain user behavior information corresponding to interaction with a first media object from a user, the first media object including a first customizable media object element and a second customizable media object element independent of the first customizable media object element; analyze a performance of the first media object based on the user behavior information; and update at least one of a user profile of the user or a group profile corresponding to the user using a machine learning model to adjust ratings of the first customizable media object element and the second customizable media object element based on a comparison of the performance of the first media object to a second custom object including at least one of the first customizable media object element or the second customizable media object element.

A server as an example of a menu recommendation system includes an evaluator, a processing unit, and an actual usage record acquirer. The evaluator recommends menus for a target period. The processing unit presents the menus recommended by the evaluator to a user. The actual usage record acquirer acquires, from the user, an actual usage record of the menus recommended by the evaluator at an arbitrary timing in the target period. When a difference occurs between first information regarding content of the menus recommended by the evaluator and second information regarding the actual usage record during a period from a start of the target period to the timing, the evaluator performs reward processing of rewarding the user according to the difference or re-recommendation processing of re-recommending menus for a remaining period by changing the content of the recommended menus.

An output control device includes a determination unit configured to determine whether or not a person is a specific person, a processing unit configured to acquire position information of the person, and an output control unit configured to cause a first output device located in the vicinity of the person to output information according to the person on the basis of personal information about the person determined to be the specific person by the determination unit and the position information acquired by the processing unit, wherein the output control unit is configured to cause a second output device to output the information output by the first output device in continuation with the output of the first output device if the person has moved from the vicinity of the first output device to the vicinity of the second output device.