Naver had two patents in edtech during Q1 2024. The patent filed by Naver Corp in Q1 2024 describes a sampling system that utilizes an energy-based model to generate non-negative scores for input with discrete classifications. The system includes a sampling module that generates samples from a probability distribution of the EBM using a proposal distribution, sets a probability of acceptance for the sample, and discards the sample based on certain criteria. GlobalData’s report on Naver gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Naver had no grants in edtech as a theme in Q1 2024.
Recent Patents
Application: Sampling from discrete energy-based models with quality/efficiency trade-off (Patent ID: US20240037184A1)
The patent filed by Naver Corp. describes a sampling system that includes an energy-based model (EBM) generating non-negative scores for inputs with discrete classifications and a sampling module that generates samples from a probability distribution of the EBM using a proposal distribution. The system sets a probability of acceptance for the sample based on various factors and discards the sample if a randomly determined distribution value exceeds the acceptance probability.
The sampling system further involves adjusting parameters based on the difference between the probability of the sample and a target probability, ensuring an acceptance rate of samples does not fall below a predetermined minimum. Additionally, the system can be applied to a question answering system where the input is a question, and the system outputs the sample as the answer when the distribution value is less than the probability of acceptance. The method involves generating samples from the EBM, setting acceptance probabilities, and discarding samples based on distribution values, with adjustments made to maintain an adequate acceptance rate. The system can be used in various applications, including question answering systems, to provide accurate and efficient sampling processes.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
