18607949. METADATA TAG IDENTIFICATION simplified abstract (eBay Inc.)
METADATA TAG IDENTIFICATION
Organization Name
Inventor(s)
Dingxian Wang of New Castle WA (US)
METADATA TAG IDENTIFICATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 18607949 titled 'METADATA TAG IDENTIFICATION
Simplified Explanation
This patent describes a method for automatically identifying metadata tags for videos by extracting content features from the video and encoding them into a common data structure using a recurrent neural network (RNN) model. The encoded data is then decoded to identify metadata tags to be associated with the video on a social content platform based on user group tag data.
- Content features are extracted from videos
- Features are from at least two different modalities
- Features are encoded into a common data structure using an RNN model
- Decoding is based on user group tag data for social content platform users
Key Features and Innovation
- Extraction of content features from videos
- Encoding of features into a common data structure using an RNN model
- Decoding of the common data structure to identify metadata tags
- Utilization of user group tag data for decoding process
Potential Applications
This technology can be applied in social media platforms, video sharing websites, content recommendation systems, and digital marketing campaigns.
Problems Solved
This technology addresses the challenge of automatically identifying relevant metadata tags for videos, which can improve content discoverability and user engagement on social media platforms.
Benefits
- Enhanced video metadata tagging process
- Improved content discoverability
- Increased user engagement on social media platforms
Commercial Applications
- Social media marketing
- Video content optimization
- Digital advertising campaigns
Prior Art
Readers can explore prior research on video content analysis, metadata tagging algorithms, and neural network models for content classification.
Frequently Updated Research
Stay updated on advancements in video content analysis, machine learning algorithms for metadata tagging, and social media platform optimization strategies.
Questions about Automatic Metadata Tag Identification for Videos
How does this technology improve user engagement on social media platforms?
This technology enhances user engagement by ensuring that videos are associated with relevant metadata tags, making them more discoverable to users interested in specific topics.
What are the potential implications of this technology for digital marketing campaigns?
This technology can significantly impact digital marketing campaigns by improving the targeting and relevance of video content to specific audience segments, leading to higher engagement and conversion rates.
Original Abstract Submitted
A method for automatic metadata tag identification for videos is described. Content features are extracted from a video into respective data structures. The extracted content features are from at least two different feature modalities. The respective data structures are encoded into a common data structure using an encoder of a recurrent neural network (RNN) model. The common data structure is decoded using a decoder of the RNN model to identify content platform metadata tags to be associated with the video on a social content platform. Decoding is based on group tag data for users of the social content platform that identifies groups of the users and corresponding group metadata tags of interest for the groups of users.