Qualcomm incorporated (20240214797). MITIGATING MISINFORMING ROGUE ACTORS IN PERCEPTIVE WIRELESS COMMUNICATIONS simplified abstract
Contents
MITIGATING MISINFORMING ROGUE ACTORS IN PERCEPTIVE WIRELESS COMMUNICATIONS
Organization Name
Inventor(s)
Himaja Kesavareddigari of Bridgewater NJ (US)
Kapil Gulati of Belle Mead NJ (US)
Hong Cheng of Basking Ridge NJ (US)
Qing Li of Princeton Junction NJ (US)
Kyle Chi Guan of New York NY (US)
Mahmoud Ashour of San Diego CA (US)
MITIGATING MISINFORMING ROGUE ACTORS IN PERCEPTIVE WIRELESS COMMUNICATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240214797 titled 'MITIGATING MISINFORMING ROGUE ACTORS IN PERCEPTIVE WIRELESS COMMUNICATIONS
Simplified Explanation: The patent application describes an apparatus that can receive indications from a network entity regarding the categorization of data elements transmitted by a wireless device. If the data is classified as misinformation, the apparatus will exclude it from being used in a machine learning procedure. The apparatus can also receive criteria for requesting a reevaluation of the categorization and transmit data elements based on meeting those criteria.
Key Features and Innovation:
- Apparatus receives indications of data categorization from a network entity.
- Excludes misinformation data from propagation in a machine learning procedure.
- Can request a reevaluation of data categorization based on set criteria.
- Transmits data elements to the network entity for reevaluation.
Potential Applications: This technology could be applied in social media platforms to filter out misinformation and improve the quality of data used for machine learning algorithms.
Problems Solved:
- Filtering out misinformation data.
- Enhancing the accuracy of machine learning procedures.
- Improving the reliability of data used in algorithms.
Benefits:
- Increased accuracy in machine learning models.
- Reduction of misinformation propagation.
- Enhanced data quality for decision-making processes.
Commercial Applications: Potential commercial applications include social media platforms, online news outlets, and e-commerce websites looking to improve data quality and combat misinformation.
Prior Art: Readers can explore prior art related to data categorization, misinformation filtering, and machine learning procedures in the field of information technology and artificial intelligence.
Frequently Updated Research: Stay updated on advancements in data filtering technologies, machine learning algorithms, and misinformation detection methods to enhance the effectiveness of the described apparatus.
Questions about Data Categorization: 1. How does the apparatus determine if data elements are categorized as misinformation? 2. What are the implications of excluding data from propagation in a machine learning procedure based on categorization criteria?
Original Abstract Submitted
an apparatus may be a ue configured to receive, from a network entity associated with a machine learning procedure, a first indication that a first set of data elements transmitted by the wireless device at a first time is categorized as misinformation and that, based on the categorization of the first set of data elements as misinformation, the network entity will temporarily exclude data from the wireless device from propagation as input for a subsequent machine learning procedure. the apparatus may further be configured to receive a second indication of a set of criteria for requesting a reevaluation of the categorization and transmit, based on meeting one or more criteria in the set of criteria, a second set of data elements to the network entity at a second time.
