Abstract: A system and method for generating a digital media plan. The method includes extracting advertisement features from an advertisement image; generating at least one prompt for a campaign dimension based on one or more of the extracted advertisement features; feeding the at least one prompt for each respective campaign dimension based on one or more extracted advertisement features to a target large language model; receiving responses to the prompts of the target large language models; and aggregating the answers to generate a digital media plan.

Abstract: A system and method for centralized crawling and extracting data points of a webpage using a centralized crawler system is provided. The method includes crawling requested webpage data, wherein the requested webpage data is selected based on a plurality of rules and includes a hypertext markup language (HTML) layer and metadata of a requested webpage; extracting at least one data point that indicate a main element that describes contents of the requested webpage; generating at least one enriched data point that provides additional information on the at least one extracted data point, wherein the additional information is collected from a plurality of data analysis systems (DASs); and creating a structured dataset of the requested webpage data based on the at least one extracted data point.

Abstract: A method and system for enriching bid requests for real-time bidding on a digital advertisement placement are provided. The method comprises processing a received bid request to extract at least one data point, wherein the bid request is received from a website requesting placement of a digital advertisement; causing generation of at least one enriched data point based on the at least one extracted data point; and associating the at least one enriched data point with the received bid request to allow a refined real-time bidding on a placement of a digital advertisement in a webpage of the website in response to the bid on the received bid request.

Abstract: A system and method for optimizing media targeting for placement of digital advertisements. The method includes creating, based on a performance goal and historical data, a first dynamic category version that includes at least one category attribute; identifying at least one first matching advertisement (ad) request based on the first dynamic category version, wherein the at least one first matching ad request is bid on for placement of advertisements; in response to the placement of advertisements, gathering feedback data on performance of served advertisements; identifying, based on the gathered feedback data, at least one potential category attribute; updating the first dynamic category version to create a second dynamic category version based on a portion of the identified at least one potential category attribute; and identifying at least one second matching ad request for bidding based on the second dynamic category version.

Abstract: The present system incorporates mobile computing devices to play games, such as electronic pull-tabs, in a plurality of venues, each having a local wireless network. Each network communicates with a central system that generates decks of game outcomes and associated awards. All wagers and awards for each game are tracked on the central system, which also provides each game award and associated outcome from a deck stored on the central system.

Abstract: The present system incorporates mobile computing devices to play games, such as electronic pull-tabs, in a plurality of venues, each having a local wireless network. Each network communicates with a central system that generates decks of game outcomes and associated awards. All wagers and awards for each game are tracked on the central system, which also provides each game award and associated outcome from a deck stored on the central system.

Abstract: A method and system for enriching bid requests for real-time bidding on a digital advertisement placement are provided. The method comprises processing a received bid request to extract at least one data point, wherein the bid request is received from a website requesting placement of a digital advertisement; causing generation of at least one enriched data point based on the at least one extracted data point; and associating the at least one enriched data point with the received bid request to allow a refined real-time bidding on a placement of a digital advertisement in a webpage of the website in response to the bid on the received bid request.

Abstract: The present system incorporates mobile computing devices to play games, such as electronic pull-tabs, in a plurality of venues, each having a local wireless network. Each network communicates with a central system that generates decks of game outcomes and associated awards. All wagers and awards for each game are tracked on the central system, which also provides each game award and associated outcome from a deck stored on the central system.

Abstract: The present system incorporates mobile computing devices to play games, such as electronic pull-tabs, in a plurality of venues, each having a local wireless network. Each network communicates with a central system that generates decks of game outcomes and associated awards. All wagers and awards for each game are tracked on the central system, which also provides each game award and associated outcome from a deck stored on the central system.

Abstract: The present system incorporates mobile computing devices to play games, such as electronic pull-tabs, in a plurality of venues, each having a local wireless network. Each network communicates with a central system that generates decks of game outcomes and associated awards. All wagers and awards for each game are tracked on the central system, which also provides each game award and associated outcome from a deck stored on the central system.

Abstract: The present system incorporates mobile computing devices to play games, such as electronic pull-tabs, in a plurality of venues, each having a local wireless network. Each network communicates with a central system that generates decks of game outcomes and associated awards. All wagers and awards for each game are tracked on the central system, which also provides each game award and associated outcome from a deck stored on the central system.

Abstract: The present system incorporates mobile computing devices to play games, such as electronic pull-tabs, in a plurality of venues, each having a local wireless network. Each network communicates with a central system that generates decks of game outcomes and associated awards. All wagers and awards for each game are tracked on the central system, which also provides each game award and associated outcome from a deck stored on the central system.

Abstract: The present system incorporates mobile computing devices to play games, such as electronic pull-tabs, in a plurality of venues, each having a local wireless network. Each network communicates with a central system that generates decks of game outcomes and associated awards. All wagers and awards for each game are tracked on the central system, which also provides each game award and associated outcome from a deck stored on the central system.

Abstract: Systems and methods are described for training a predictive model using social media data for artists from a period of time prior to the immediate past year and for using the trained model on social media metrics collected in the immediate prior year for the same set of artists to predict probability of success in a future period of time. The “training set” of artists includes both artists that have experienced success in the past year and artists that have yet to experience any success according to selected criteria. The predictive model predicts the next big musical success in the entertainment marketplace.

Abstract: The present system incorporates mobile computing devices to play games, such as electronic pull-tabs, in a plurality of venues, each having a local wireless network. Each network communicates with a central system that generates decks of game outcomes and associated awards. All wagers and awards for each game are tracked on the central system, which also provides each game award and associated outcome from a deck stored on the central system.