International business machines corporation (20240129582). AUTOMATIC CONTENT CLASSIFICATION AND AUDITING simplified abstract
Contents
- 1 AUTOMATIC CONTENT CLASSIFICATION AND AUDITING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 AUTOMATIC CONTENT CLASSIFICATION AND AUDITING - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
AUTOMATIC CONTENT CLASSIFICATION AND AUDITING
Organization Name
international business machines corporation
Inventor(s)
Yi Chen Zhong of shanghai (CN)
Yuan Yuan Ding of Shanghai (CN)
AUTOMATIC CONTENT CLASSIFICATION AND AUDITING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240129582 titled 'AUTOMATIC CONTENT CLASSIFICATION AND AUDITING
Simplified Explanation
The abstract describes a patent application for a content classification model that determines the category of a piece of content and removes it if it is deemed inappropriate.
- Content classification model trained using labelled training content
- Determines label for first content
- Classifies first content into category using label
- Removes first content if classified as inappropriate
Potential Applications
The technology could be applied in various industries such as social media platforms, online marketplaces, and content moderation services to automatically filter out inappropriate content.
Problems Solved
1. Efficient content moderation: Helps platforms quickly identify and remove inappropriate content. 2. Enhancing user experience: Ensures users are not exposed to harmful or offensive material.
Benefits
1. Time-saving: Automates the process of content moderation. 2. Improved safety: Creates a safer online environment for users. 3. Compliance: Helps platforms comply with regulations regarding inappropriate content.
Potential Commercial Applications
"Automated Content Moderation Technology for Safer Online Environments"
Possible Prior Art
Prior art may include existing content moderation tools and algorithms used by social media platforms and online forums to filter out inappropriate content.
Unanswered Questions
How does the model handle new or previously unseen types of inappropriate content?
The model may need to be regularly updated with new training data to adapt to emerging trends in inappropriate content.
What measures are in place to prevent false positives in content classification?
There should be mechanisms to review and correct misclassified content to avoid mistakenly removing appropriate content.
Original Abstract Submitted
using labelled training content, a content classification model is trained. using the trained content classification model, a label describing a first content is determined. the first content is classified into a category in a set of categories using the label. responsive to the first content being classified into a category of inappropriate content, the first content is removed from a storage location.
