Optimization of Patent Retrieval Strategy Based on Classification Number Similarity Coefficient and Concentration Index
This paper aims to propose and validate an optimized patent retrieval strategy by deeply analyzing the similarity coefficient and concentration index of patent classification numbers,with the hope of enhancing the efficiency and accuracy of patent retrieval. The study first clarifies the crucial role of classification numbers in patent retrieval,and then elaborates in detail on the concepts,calculation methods,and applications of classification number similarity coefficients and concentration indices in wide patent retrieval scenarios. Through empirical analysis and validation experiments,the results show that adopting this strategy can improve the efficiency and accuracy of patent retrieval,especially in fields with highly concentrated technological classifications. Additionally,the study reveals the limitations of the current strategy and proposes directions for future improvements. Overall,this paper provides practical guidance and strategic suggestions for the retrieval work of patent searcher,which is of certain significance for enhancing examination efficiency and quality of patent retrieval.
patent retrievalclassification number similarity coefficientclassification number concentration indexretrieval strategy
万方数据
维普
