Rakuten Group had 48 patents in artificial intelligence during Q4 2023. The Rakuten Group Inc filed patents in Q4 2023 for various information processing devices and apparatuses utilizing machine learning models. These patents include detecting devices for identifying genuine or fraudulent articles, information processing devices for estimating user effects and predicting user behavior, as well as classifying machine-learning capabilities of user devices in a telecommunication network. Additionally, there are patents for information processing apparatuses that predict disease risks for users based on social relationships and user features. GlobalData’s report on Rakuten Group gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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Rakuten Group grant share with artificial intelligence as a theme is 22% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Detecting device, detecting method, machine learning device, machine learning method, and machine learning model (Patent ID: US20230419081A1)
The patent filed by Rakuten Group Inc. describes a detecting device that utilizes two machine learning models to determine the authenticity of article information with multiple modalities. The first model generates genuine or fraudulent article information, while the second model discriminates whether the information is genuine. The device includes sections for obtaining the article information and estimating its authenticity using the second machine learning model. The device can process various types of data, such as images, text, numerical data, and attributes related to articles, exhibitors, or sellers.
Additionally, the patent includes claims for a detecting method executed by a computer, a computer-readable recording medium storing a detecting program, a machine learning device, a machine learning method, and a machine learning model capable of discriminating the authenticity of article information. These claims outline the process of mutual learning between the two machine learning models to generate and evaluate genuine or fraudulent article information. The patent emphasizes the importance of utilizing machine learning techniques to enhance the accuracy and efficiency of detecting fraudulent activities related to articles and sellers.
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