Abstract: A visitation tracking system tracks user visitation to locations of interest to generate and report visualizations of the user visitation data. The visitation tracking system may be or include a group of one or more server machines configured to receive a user input specifying a location of interest, cause display of a presentation of a set of proximity borders within a region in response to the user input specifying the location of interest, wherein the region is based on the location of interest, receives a selection of a region to monitor (e.g., proximity borders, geo-fences), detects entries of client devices to a geo-fence represented by the region to monitor, and causes display of a notification in response to the detection of the entries.

Abstract: Disclosed are systems, methods, and computer-readable storage media to present content on an electronic display. In one aspect, a method includes identifying a first candidate content and a second candidate content for presentation on an electronic display, determining a first probability and a second probability that the first candidate content and the second candidate content respectively will elicit a particular type of input response, determining a first weight and a second weight based on the first probability and the second probability respectively, selecting either the first content or the second content based on the first weight and the second weight; and presenting the selected content on the electronic display.

Abstract: A system and method for determining user intent and providing targeted advertising using chatbot interactions is disclosed. The system receives user prompts during chat sessions with a chatbot and generates responses using a large language model. User intent is extracted by analyzing the chat conversations using natural language processing and machine learning techniques. The extracted user intent, comprising weighted keywords and concepts, is used to create a user intent profile. Targeted advertising content is generated based on the user intent profile and provided to the user during subsequent platform interactions. The large language model is continuously retrained using user engagement data to improve intent modeling accuracy. User privacy is maintained by limiting context extraction to chatbot conversations. The system enables personalized and relevant advertising by inferring user intent through conversational interactions.

Abstract: Systems and methods are provided for receiving a request for lookalike data, the request for lookalike data comprising seed data and generating sample data from the seed data and from user data for a plurality of users, to use in a lookalike model training. The systems and methods further provide for capturing a snapshot of social graph data for a plurality of users and computing social graph features based on the seed data and the user data for the plurality of users, training a lookalike model based on the sample data and the computed social graph features to generate a trained lookalike model, generating a lookalike score for each user of the plurality of users in the user data using the trained lookalike model, and generating a list comprising a unique identifier for each user of the plurality of users and an associated lookalike score for each unique identifier.

Abstract: Disclosed are systems, methods, and computer-readable storage media to present content on an electronic display. In one aspect, a method includes identifying a first candidate content and a second candidate content for presentation on an electronic display, determining a first probability and a second probability that the first candidate content and the second candidate content respectively will elicit a particular type of input response, determining a first weight and a second weight based on the first probability and the second probability respectively, selecting either the first content or the second content based on the first weight and the second weight; and presenting the selected content on the electronic display.

Abstract: Systems and methods are provided for receiving a request for lookalike data, the request for lookalike data comprising seed data and generating sample data from the seed data and from user data for a plurality of users, to use in a lookalike model training. The systems and methods further provide for capturing a snapshot of social graph data for a plurality of users and computing social graph features based on the seed data and the user data for the plurality of users, training a lookalike model based on the sample data and the computed social graph features to generate a trained lookalike model, generating a lookalike score for each user of the plurality of users in the user data using the trained lookalike model, and generating a list comprising a unique identifier for each user of the plurality of users and an associated lookalike score for each unique identifier.

Abstract: A visitation tracking system tracks user visitation to locations of interest to generate and report visualizations of the user visitation data. The visitation tracking system may be or include a group of one or more server machines configured to receive a user input specifying a location of interest, cause display of a presentation of a set of proximity borders within a region in response to the user input specifying the location of interest, wherein the region is based on the location of interest, receives a selection of a region to monitor (e.g., proximity borders, geo-fences), detects entries of client devices to a geo-fence represented by the region to monitor, and causes display of a notification in response to the detection of the entries.

Abstract: A visitation tracking system tracks user visitation to locations of interest to generate and report visualizations of the user visitation data. The visitation tracking system may be or include a group of one or more server machines configured to receive a user input specifying a location of interest, cause display of a presentation of a set of proximity borders within a region in response to the user input specifying the location of interest, wherein the region is based on the location of interest, receives a selection of a region to monitor (e.g., proximity borders, geo-fences), detects entries of client devices to a geo-fence represented by the region to monitor, and causes display of a notification in response to the detection of the entries.

Abstract: Disclosed are systems, methods, and computer-readable storage media to present content on an electronic display. In one aspect, a method includes identifying a first candidate content and a second candidate content for presentation on an electronic display, determining a first probability and a second probability that the first candidate content and the second candidate content respectively will elicit a particular type of input response, determining a first weight and a second weight based on the first probability and the second probability respectively, selecting either the first content or the second content based on the first weight and the second weight; and presenting the selected content on the electronic display.

Abstract: A visitation tracking system tracks user visitation to locations of interest to generate and report visualizations of the user visitation data. The visitation tracking system may be or include a group of one or more server machines configured to receive a user input specifying a location of interest, cause display of a presentation of a set of proximity borders within a region in response to the user input specifying the location of interest, wherein the region is based on the location of interest, receives a selection of a region to monitor (e.g., proximity borders, geo-fences), detects entries of client devices to a geo-fence represented by the region to monitor, and causes display of a notification in response to the detection of the entries.

Abstract: A visitation tracking system tracks user visitation to locations of interest to generate and report visualizations of the user visitation data. The visitation tracking system may be or include a group of one or more server machines configured to receive a user input specifying a location of interest, cause display of a presentation of a set of proximity borders within a region in response to the user input specifying the location of interest, wherein the region is based on the location of interest, receives a selection of a region to monitor (e.g., proximity borders, geo-fences), detects entries of client devices to a geo-fence represented by the region to monitor, and causes display of a notification in response to the detection of the entries.

Abstract: Disclosed are systems, methods, and computer-readable storage media to present content on an electronic display. In one aspect, a method includes identifying a first candidate content and a second candidate content for presentation on an electronic display, determining a first probability and a second probability that the first candidate content and the second candidate content respectively will elicit a particular type of input response, determining a first weight and a second weight based on the first probability and the second probability respectively, selecting either the first content or the second content based on the first weight and the second weight; and presenting the selected content on the electronic display.

Abstract: Systems and methods are provided for receiving a request for lookalike data, the request for lookalike data comprising seed data and generating sample data from the seed data and from user data for a plurality of users, to use in a lookalike model training. The systems and methods further provide for capturing a snapshot of social graph data for a plurality of users and computing social graph features based on the seed data and the user data for the plurality of users, training a lookalike model based on the sample data and the computed social graph features to generate a trained lookalike model, generating a lookalike score for each user of the plurality of users in the user data using the trained lookalike model, and generating a list comprising a unique identifier for each user of the plurality of users and an associated lookalike score for each unique identifier.

Abstract: Methods and systems for extracting intents and intent profiles of users, as inferred from the different activities they execute and data they share on social media sites, and then (i) monetization of such intents via targeted advertisements, and (ii) enhancement of user experience via organization of their contact lists and conversations and posts based on their content and conceptual context.

Abstract: Systems and methods are provided for receiving a request for lookalike data, the request for lookalike data comprising seed data and generating sample data from the seed data and from user data for a plurality of users, to use in a lookalike model training. The systems and methods further provide for capturing a snapshot of social graph data for a plurality of users and computing social graph features based on the seed data and the user data for the plurality of users, training a lookalike model based on the sample data and the computed social graph features to generate a trained lookalike model, generating a lookalike score for each user of the plurality of users in the user data using the trained lookalike model, and generating a list comprising a unique identifier for each user of the plurality of users and an associated lookalike score for each unique identifier.

Abstract: Methods and systems for extracting intents and intent profiles of users, as inferred from the different activities they execute and data they share on social media sites, and then (i) monetization of such intents via targeted advertisements, and (ii) enhancement of user experience via organization of their contact lists and conversations and posts based on their content and conceptual context.

Abstract: A visitation tracking system tracks user visitation to locations of interest to generate and report visualizations of the user visitation data. The visitation tracking system may be or include a group of one or more server machines configured to receive a user input specifying a location of interest, cause display of a presentation of a set of proximity borders within a region in response to the user input specifying the location of interest, wherein the region is based on the location of interest, receives a selection of a region to monitor (e.g., proximity borders, geo-fences), detects entries of client devices to a geo-fence represented by the region to monitor, and causes display of a notification in response to the detection of the entries.

Abstract: A visitation tracking system tracks user visitation to locations of interest to generate and report visualizations of the user visitation data. The visitation tracking system may be or include a group of one or more server machines configured to receive a user input specifying a location of interest, cause display of a presentation of a set of proximity borders within a region in response to the user input specifying the location of interest, wherein the region is based on the location of interest, receives a selection of a region to monitor (e.g., proximity borders, geo-fences), detects entries of client devices to a geo-fence represented by the region to monitor, and causes display of a notification in response to the detection of the entries.

Abstract: Methods and systems for extracting intents and intent profiles of users, as inferred from the different activities they execute and data they share on social media sites, and then (i) monetization of such intents via targeted advertisements, and (ii) enhancement of user experience via organization of their contact lists and conversations and posts based on their content and conceptual context.

Abstract: Methods and systems for extracting intents and intent profiles of users, as inferred from the different activities they execute and data they share on social media sites, and then (i) monetization of such intents via targeted advertisements, and (ii) enhancement of user experience via organization of their contact lists and conversations and posts based on their content and conceptual context.