Big Data Related Patent Retrieval System Based on Filtering Rules

Abstract

In the information age, patents are an important carrier of scientific research achievements. How to protect patents and effectively transmit them has become an important development measure in the current information age. A big data-related patent retrieval technology based on filtering rules is proposed to address issues such as poor keyword and phrase retrieval positioning in patent analysis. This new technology combines multiple filtering and retrieval methods and builds a data storage and transmission system. The model achieved the best performance when the threshold was set to 100. The frequency of using the training set before and after keyword filtering increased by 10 and the frequency of using the test set before and after keyword filtering increased by 16. The Euclidean distance of the research method decreased by 0.883 compared to other methods. The mean value increased by 0.1611 compared to other methods. The cosine value increased by 0.4300 compared to other methods. Therefore, the new method has a better filtering effect on patent keywords compared to other methods. This has a good guiding effect on the retrieval of big data-related patents.