Patent classifications are the original patent searching tools and remain among the most useful ways to categorize and index related prior art. Classifications, by definition, are groups of patent documents of similar subject matter. Several major patent classification systems exist, including US, IPC, ECLA, Japanese F-Index and F-Term, and DEKLA. In previous posts, we have discussed how patent searching by classification works and why it’s worthwhile. To check out those posts, see parts one and two of the “Classified Information” series.
Patent classifications can be vitally important in conducting a patent analysis project, and today we’ll show you how to utilize classification systems to pare down your pool of patent documents under review in addition to potentially finding new documents of interest.
Last time, in Learn Practical Patent Analysis: A Case Study (Installment 2), we discussed how manual de-duplication can reduce the redundant patent documents returned to us in our first full text search query. Barring that, we discussed how patent families could be used as a de-duplication tool to limit certain closely related patent applications from overwhelming the project: removing family duplicates in the data set is desirable because it reduces the amount of time needed to perform both manual and statistical analysis processes, and it focuses the analysis on the inventive concepts rather than the patent documents. To keep this case study concise and to the point I’ve chosen an automatic family de-duplication process to represent each patent family as one object. The analysis that follows is based on this method, but different patent analysis studies require different methods, a point not lost on our commenters last week.
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Filed under: Case Study, Patent Analysis | Tagged: analysis, classification, IPC classification, patent analysis, US patent classification | 5 Comments »