Event-Based Content Distribution Using Search, Interest, and Location Signals
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Solution Overview
Problem
Existing content distribution systems struggle to effectively reach users interested in live events, as it is difficult to identify the right combination of distribution keywords and time periods to target users during the event, especially when users do not directly search for event-related resources.
Innovation Solution
An event-based content distribution system that determines user interest in live events by analyzing search query trends and user attributes, allowing content sponsors to select a live event, which automatically sets distribution criteria such as time and geographic regions, enabling content delivery during relevant periods and to interested users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If content distribution systems use traditional keyword-based targeting, then they can deliver content to users, but they fail to effectively reach users interested in live events who do not directly search for event-related resources
Solution Approach 1:
The patent introduces an intermediary event-based distribution mechanism that connects content sponsors with users interested in live events. This intermediary system analyzes search query trends and user attributes to identify users interested in events, then delivers content to them even when users are accessing unrelated resources, without requiring direct event-related searches from users.
Solution Approach 2:
The system implements feedback loops by continuously monitoring search query trends, user attributes, and event data to dynamically identify and update the set of users interested in live events. This feedback mechanism allows the system to adapt to changing user interests and improve content delivery accuracy over time.
2Ease of operation
If content sponsors manually specify distribution parameters, then they can control content distribution, but it becomes difficult to identify the right combination of keywords and time periods for live events
Solution Approach 1:
The system enables self-service by automatically generating event-based distribution parameters (time periods, geographic regions, user attributes) from event data and search query trends. Content sponsors simply need to select a live event, and the system automatically configures all necessary distribution parameters, eliminating the need for manual specification of complex parameter combinations.
Solution Approach 2:
The system performs preliminary actions by pre-identifying users interested in live events based on their attributes and search behavior before content distribution occurs. This allows the system to have distribution parameters ready in advance, making the content delivery process smoother and more efficient.
3Loss of time
If the system targets users during live events, then content delivery becomes timely, but it requires automatic setting of distribution criteria which increases system complexity
Solution Approach 1:
The system achieves multi-functionality by using a single event-based distribution mechanism that simultaneously handles multiple tasks: identifying interested users, determining optimal time periods, defining geographic regions, and selecting appropriate user attributes. This universal approach simplifies the overall system architecture compared to having separate mechanisms for each function.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for distributing content are disclosed. In one aspect, a method includes storing, in a data structure, data specifying a future live event. An opportunity to provide the specified content to a user at a user device is identified. It is determined that (i) a time of the opportunity is between a start time and an end time for the live event, (ii) that a user device is located in a same geographic region as the live event based on geographical data provided by the user device, and (iii) the user is interested in the live event based on attributes of the user matching attributes of other users that were identified as interested in the live event (e.g., based on evaluation of online search data). The content is provided for display at the user device.