Video-Hosting Keyword Extraction for Scene-Based Media Search
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Solution Overview
Problem
Traditional keyword generation techniques for media content search systems lack accurate associations between keywords and media content identifiers, particularly when users query using memorable scenes instead of titles, leading to irrelevant search results.
Innovation Solution
Generate media content keywords based on user-generated video content from video-hosting websites, using relevance scores derived from the number of uploads and views of video clips related to the media program, to create a comprehensive keyword database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional keyword generation techniques using word document frequency analysis and back-link reference analysis of limited sources are used, then the keyword generation process is simple, but the associations between keywords and media content identifiers are inaccurate and incomplete, leading to irrelevant search results
Solution Approach 1:
The patent transitions from analyzing text-based sources (plot summaries) to analyzing video-based sources (video clips uploaded to video-hosting websites). This dimensional change allows the system to capture memorable scenes and visual content that text descriptions cannot represent, thereby improving keyword association accuracy with memorable scenes while utilizing a different type of data source
Solution Approach 2:
The system extracts and analyzes video clips from video-hosting websites that are copies or excerpts of media program content. By analyzing these copied video segments and their associated metadata (titles, descriptions, user comments), the system generates keywords that accurately reflect memorable scenes without requiring direct access to the original media content
2Measurement precision
If video-hosting website content is used to generate keywords, then the keyword associations become more accurate and comprehensive, but the data processing complexity and time requirements increase
Solution Approach 1:
The system extracts only the necessary and relevant information from video-hosting website content, such as video titles, descriptions, and user comments that contain keywords. Rather than processing entire video files or all website data, it selectively extracts text-based metadata and analytical signals, significantly reducing processing time while maintaining keyword generation accuracy
Solution Approach 2:
The system performs preliminary analysis of video-hosting website content to identify and extract potential keywords before the actual keyword generation process. By pre-processing and indexing commonly occurring terms and phrases from video metadata, the system reduces the computational burden during the main keyword generation phase, thereby reducing overall processing time
Data Source
AI summary
Systems and methods for generating media program keywords based on a video-hosting website are disclosed herein. Control circuitry identifies, on the video-hosting website, video content items that include at least a portion of a media program. The media program has a media program identifier and the video content items have respective titles, each including one or more terms. The control circuitry identifies a term included in more than one of the titles and identifies a group of the video content items that have the term included in their title. Based on the video-hosting website, the control circuitry determines a cumulative number of rankings of the video content items within the group and generates a relevance score for the term based on the cumulative number of rankings. The control circuitry stores the term and the relevance score in a keyword database in association with the media program identifier.