Video Search Control with Pre-populated Channel Suggestions
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Solution Overview
Problem
Video sharing websites face inefficiencies in allowing advertisers to find relevant videos for advertising campaigns, as users spend considerable time searching for suitable videos, and existing systems lack personalized suggestions based on historical user preferences.
Innovation Solution
Implementing a search control that provides pre-populated suggestion lists for video content items, based on users' historical channel selections and search queries, allowing advertisers to filter results and associate videos with advertisements more efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If users manually search for video content items in a repository, then they can find relevant videos for advertising campaigns, but the process consumes considerable time and lacks personalization
Solution Approach 1:
The system performs preliminary actions by analyzing users' historical channel selections and search queries before the user needs to search again. It pre-processes this historical data to generate personalized suggestion lists that are automatically presented to users, eliminating the need for them to start from scratch in their video search process.
Solution Approach 2:
The system enables self-service by automatically generating and updating personalized video suggestions based on users' own historical behavior data. The suggestions adapt and refine themselves over time as the system continuously learns from users' search patterns and channel selections, making the search process increasingly efficient without additional user effort.
2Productivity
If the system provides personalized video suggestions based on historical data, then search efficiency improves, but system complexity increases
Solution Approach 1:
The system segments the complex task of video recommendation into distinct functional modules: historical data collection, channel selection analysis, search query processing, suggestion generation, and result presentation. Each module handles a specific aspect of the recommendation process, making the overall system more manageable and maintainable despite its sophisticated functionality.
Solution Approach 2:
The system achieves multi-functionality by using a unified approach that handles multiple types of user interactions (channel selections, search queries) through a single analytical framework. This same framework serves both to understand user preferences and to generate personalized suggestions, reducing the need for separate specialized systems.
Data Source
AI summary
Methods, systems, and apparatus, including computer program products, for providing efficient searching of video content. In one aspect, a method includes providing a search control associated with video content items, the search control for receiving search queries for identifying video content items associated with one or more channels in a video sharing environment. A search query is received from a user logged into one of the video sharing environment or a content distribution system. One or more matching video content items are located from the repository based on the search query. A selection of one or more of the video content items is received. A channel associated with the selected video content items is determined. Providing the search control further includes providing a pre-populated suggestion list for selecting a filter criteria for locating a video content item based on the stored historical channel selections associated with the user.