Snap inc. (20240354508). NAMED ENTITY RECOGNITION VISUAL CONTEXT AND CAPTION DATA simplified abstract
Contents
NAMED ENTITY RECOGNITION VISUAL CONTEXT AND CAPTION DATA
Organization Name
Inventor(s)
Leonardo Ribas Machado das Neves of Marina Del Rey CA (US)
Vitor Rocha de Carvalho of San Diego CA (US)
Ning Zhang of Los Angeles CA (US)
NAMED ENTITY RECOGNITION VISUAL CONTEXT AND CAPTION DATA - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240354508 titled 'NAMED ENTITY RECOGNITION VISUAL CONTEXT AND CAPTION DATA
The abstract of a patent application discusses how an entity recognition system can identify named entities in a multimodal message using a visual attention-based mechanism.
- The system generates a visual context representation from an image and caption.
- It uses the visual context representation to identify terms in the caption as named entities.
Potential Applications: - Social media content moderation - Image and caption analysis for marketing purposes - Enhancing search engine optimization for visual content
Problems Solved: - Efficiently identifying named entities in multimodal messages - Improving the accuracy of entity recognition in visual content
Benefits: - Streamlining content analysis processes - Enhancing the understanding of visual messages - Increasing the effectiveness of targeted advertising
Commercial Applications: - Social media platforms - Marketing agencies - E-commerce websites
Questions about Entity Recognition System: 1. How does the visual attention-based mechanism improve entity recognition in multimodal messages?
- The visual attention mechanism focuses on relevant parts of the image to better understand the context of the caption.
2. What are the potential challenges in implementing this system on a large scale?
- Scalability and processing speed may be key challenges in deploying this technology across various platforms.
Original Abstract Submitted
a caption of a multimodal message (e.g., social media post) can be identified as a named entity using an entity recognition system. the entity recognition system can use a visual attention based mechanism to generate a visual context representation from an image and caption. the system can use the visual context representation to identify one or more terms of the caption as a named entity.
