Ricoh had 42 patents in artificial intelligence during Q4 2023. Ricoh Co Ltd filed patents in Q4 2023 for methods and apparatus related to named entity recognition, training machine reading comprehension models, and controlling communication between terminal apparatus. These patents involve processes such as generating vector representations, detecting speech data, and identifying print defects in printed media. GlobalData’s report on Ricoh gives a 360-degreee view of the company including its patenting strategy. Buy the report here.

Ricoh grant share with artificial intelligence as a theme is 40% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Method and apparatus for named entity recognition, and non-transitory computer-readable recording medium (Patent ID: US20230394240A1)

The patent filed by Ricoh Co Ltd. describes a method and apparatus for named entity recognition, involving traversing text elements in a text to identify candidate entity words and recognizing the class to which each candidate entity word belongs. This recognition process includes generating a prompt template, concatenating the text with the template to create a concatenated text, generating vector representations of the text elements, and classifying the candidate entity word based on these representations. The method also involves integration processes to obtain span representations of the candidate entity word and the use of a mask word for classification.

Furthermore, the apparatus described in the patent includes memory storing computer-executable instructions and processors to execute these instructions. The apparatus is designed to traverse text elements, recognize the class of candidate entity words, generate prompt templates, concatenate text, and perform integration processes to classify the candidate entity words. The apparatus utilizes vector representations and a softmax function to determine the probability of candidate entity words belonging to different classes, ultimately selecting the class with the highest probability. Overall, the method and apparatus aim to improve named entity recognition by utilizing prompt learning, vector representations, and integration processes for accurate classification.

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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.