Abstract
Automatic patent classification facilitates searching for previous patent documents. For TRIZ users, they would like to search for patents based on the solutions (TRIZ Inventive Principles) to the Contradictions addressed in the patents, which is different from traditional searching for prior arts based on the application fields of the inventions. For this purpose, a TRIZ-based patent classification expert system is needed. To facilitate automatic classification of patent documents according to Inventive Principles (IPs) for TRIZ users, we analyze the original 40 IPs proposed by Altshuller. Seven IPs are defined as Obscure IPs, the other 33 as Distinct IPs. Furthermore, two kinds of similarity among the Distinct IPs are defined: text similarity and meaning similarity. Then the 40 IPs are grouped into 22 new classes. Automatic classification based on 674 patent documents associated with these 22 new classes is tested and analyzed, with two issues of multi-label classification and class imbalance addressed.
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