Experimental data for the evaluation of the approach to building PDKG
We evaluate 2 key stages in building a PDKG: Extraction of entity terminology and Extraction of concept using NLP. precision and recall are the most commonly used metrics to measure the performance of extraction algorithms. Precision measures accuracy, the probability of the expected result in all extracted samples, and recall measures the completeness of the extracted result, the probability of the expected result being extracted from the original data. In the evaluation process, a certain number of Chinese patent specification body texts as well as sentences describing design knowledge in the patent were selected for experiments to evaluate the proposed method.