Rakuten Group had 43 patents in ecommerce during Q4 2023. The Rakuten Group Inc filed patents related to detecting fraudulent articles using machine learning models, creating planned event protocols for network element parameter changes, personalized customer dunning based on customer data, targeting based on social connections in a user group, and estimating attributes of a target user based on related user features in a social relationship graph. 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 ecommerce as a theme is 37% 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 with multiple modalities. The patent emphasizes the importance of utilizing machine learning techniques to enhance the detection of fraudulent activities in the context of online articles and e-commerce platforms.
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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.
