Hitachi had 185 patents in artificial intelligence during Q1 2024. Hitachi Ltd filed patents in Q1 2024 for systems and methods related to research viewpoint presentation, fault tree generation, sample collection call time prediction, work support systems, and computing apparatus with DNN computation capabilities. These inventions aim to improve relevance calculations, fault tree development, prediction accuracy, work support, and parallel computation in computing devices. GlobalData’s report on Hitachi gives a 360-degree view of the company including its patenting strategy. Buy the report here.
Hitachi grant share with artificial intelligence as a theme is 44% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Research viewpoint presentation system and research viewpoint presentation method (Patent ID: US20240104303A1)
The patent filed by Hitachi Ltd. describes a research viewpoint presentation system that calculates potential relevance levels between words in a document group based on co-occurrence rates and existing relevance levels based on actual word appearances. The system then selects pairs of words based on an index comparing potential and existing relevance levels, extracts recommended research viewpoint information for the selected pairs, and outputs this information. The system can also consider word trend information and pair trend information in the selection process, as well as user-specified words or categories.
Furthermore, the system can generate and output graphs representing the selected word pairs, with nodes representing the words and edges connecting them, along with attached information based on the index. Additionally, the system can connect nodes representing the document source to nodes representing words in the graph. Overall, the system provides a method for managing document groups, calculating relevance levels between words, selecting word pairs, extracting research viewpoint information, and presenting this information effectively through graphs.
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