Video Entity Tagging for Faster, More Accurate Recommendations
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Solution Overview
Problem
The process of actively searching for detailed information of recommended entities in videos is time-consuming and often results in inaccurate searches, affecting the search effectiveness.
Innovation Solution
Displaying information tags associated with target entities in videos, based on entity types, and providing recommendation information upon tag triggering, which allows for quick and accurate acquisition of relevant content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users actively initiate a search for recommended entities, then they can obtain detailed information, but the time and complexity of acquiring information increases
Solution Approach 1:
The system performs preliminary actions by automatically extracting entity information and generating recommendation content before the user needs it. The server proactively retrieves and prepares detailed information about recommended entities, so when users view the video, the information is already prepared and can be displayed with a single interaction, eliminating the need for users to actively search and reducing time loss.
2Loss of information
If users actively search for recommended entities, then they can obtain detailed information, but the search accuracy decreases
Solution Approach 1:
The system performs self-service by automatically identifying and extracting entity information without requiring user input. The server autonomously analyzes the video content, identifies recommended entities, retrieves their detailed information, and generates appropriate recommendation content. This eliminates the need for users to manually search, ensuring accurate information retrieval based on the system's understanding of the video context rather than user search queries.
3Loss of information
If the system displays all entity information, then information completeness improves, but the complexity of the system increases
Solution Approach 1:
The system applies segmentation by dividing entity information into different categories and displaying only the relevant segments based on the video context and user needs. Rather than displaying all possible entity information at once, the system segments the information into appropriate categories (such as entity attributes, related content, recommendations) and selectively displays them, reducing the perceived system complexity while maintaining information completeness.
Solution Approach 2:
The system implements local quality by tailoring the displayed information to specific local contexts within the video. Different entity information is displayed based on the specific video segment, entity type, and user interaction history. This localized approach ensures that only the most relevant information is displayed at any given time, reducing overall system complexity while maintaining comprehensive information availability where needed.
Data Source
AI summary
A method of information recommendation, a computer device and a storage medium are provided. The method includes: playing a target video on an information recommendation page; displaying respective information tags associated with a target entity in the target video, the respective information tags being generated according to at least one information recommendation dimension corresponding to an entity type of the target entity, different entity types corresponding to different information recommendation dimensions; and in response to triggering the information tag, displaying target recommendation information in the information recommendation dimension corresponding to the information tag.