The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of features associated with a customer, wherein the set of features includes profile data from an online professional network and one or more standardized features related to a role of the customer. Next, the system applies a set of whitelists and a set of blacklists to the features to identify a market segment for the customer. The system then uses the market segment to generate output for use in targeting the customer with an educational technology product.

A system and method allow a user to define a search request by selecting and weighting graphical icons provided on a search creation interface. The graphical icons may be selected by using an icon selection feature provided on the search creation interface. The graphical icons may further be assigned relative search weights using an icon weighting feature provided on the search creation interface. The system and method generate search results based on metadata associated with the selected ones of the graphical icons and the search weights assigned to each of the selected ones of the graphical icons. The search results may comprise a ranked list of items, such as products listed for sale on an e-commerce server.

An advertisement system and method of identifying targeted advertisements for presentation to one or more viewers. In one aspect, the invention may be a method of identifying targeted advertisements for presentation to one or more viewers, the method comprising: receiving a map based on one or more advertising groups and characterization information derived from at least one of the viewers; and transmitting to equipment associated with the viewers, one or more advertisements each having one or more advertising group identifier, wherein an advertising group identifier matches an advertising group within the map.

The present disclosure relates to systems and methods for operating an online on-demand service platform. The systems may perform the methods to: determine one or more recommendation rules for one or more activities for recommending to one or more candidate users; determine, for each of the one or more activities, one or more preset objects for the activity to achieve on the one or more candidate users; determine, for each of the one or more activities, a completion probability that each of the one or more candidate users will complete the one or more preset objects of the activity; and determine, for each of the one or more activities, at least one target user from the one or more candidate users to send a notice of the activity based on the one or more completion probabilities and the one or more recommendation rules.

A computer-implemented method for selecting a digital content, comprising: receiving a plurality of samples, each comprises a request having a plurality of values of a plurality of attributes, and associated with a success value for a Bernoulli distributed event having a campaign and a bid rate (BR) of the campaign; clustering the plurality of samples in a plurality of homogenous nodes according to respective plurality of values; identifying a group campaign with a highest valuation for each one of the plurality of nodes using triangular approximation of the Bernoulli distribution of events in the node; receiving a query from a device including a plurality of other values of the plurality of attributes; selecting one of the plurality of nodes; selecting a digital content of the group campaign with highest valuation identified for the selected node; and generating a response to the query including the selected content.

System and methods for optimizing an experience that a user can have at a website using audience segmentation data. Optimizing an experience can include creating the audience segment, from the consumer data, corresponding to the vehicle model from a plurality of vehicle models; generating a plurality of audience weights based on the sales goals data, the vehicle sales data, and the audience segment; generating an augmented consumer profile based on the plurality of audience weights and a consumer profile derived from the audience segment; applying the augmented consumer profile to personalize content on a dealership webpage; and providing the personalized content to a consumer computing device accessing the dealership webpage to optimize a consumer experience.

A method, an apparatus, and a computer program product for communication are provided in which a communications device is operable to provide an improved user experience or to improve the performance and/or operation of the communications device through use of an enriched user profile. In one aspect, the communications device may predict an event occurrence by interpreting an enriched user profile including an attribute and an enhanced informational element. The communications device may modify a functionality of a component of the device based on the predicted event occurrence. In one aspect, component modification may include presenting the contextually relevant informational element on a user interface.

A system and method for determining popularity of a video based in part on requests for the video received from a referrer, grouping videos whose popularity based on requests from referrers exceeds a threshold and displaying those videos in a channel or providing them in a web feed.

A loyalty program method for incenting a registered customer to conduct a transaction with a registered merchant. The method data mines transaction data between registered merchants and registered customers with an artificial intelligence engine operated by a supercomputer. The method predicts the likelihood that an offer having an incentive will be accepted by a registered customer by conducting a transaction with the registered merchant. The incentive can be a donation by the merchant to an entity with which the registered customer has an affinity in exchange for the registered customer by conducting a transaction with the registered merchant.

A method, non-transitory computer readable medium, apparatus, and system for content distribution are described. An embodiment of the present disclosure includes obtaining, by a user experience platform, a prompt describing an element of a content distribution campaign. A machine learning model generates a user journey based on the prompt. The user journey includes at least one touchpoint for the content distribution campaign. The user experience platform provides digital content to a user corresponding to the at least one touchpoint based on the user journey.