In a recent article, I presented an analysis of US Patent and Trademark Office (USPTO) data demonstrating that success rate for so-called ‘business method’ patent applications has fallen dramatically since the US Supreme Court issued its Alice decision in June 2014. While the difference between ‘business methods’ and other more ‘traditional’ fields of technology is particularly stark, it is more generally the case that average allowance rates at the USPTO vary considerably across the various examination Art Units (i.e. the groupings of examiners assigned to specific technical subject matters). For example, an article published by IP Watchdog in 2015, Austin Underhill of Juristat demonstrated that allowance rates across all Art Units range from less than 10% in some of the ‘business method’ units to nearly 100% in Art Unit 3659 (which covers aspects of material and article handling).
It follows that if it were possible to predict, in advance of filing, to which Art Unit a US patent application would likely be assigned, this could go some way towards predicting the prospects of success in examination.
As also mentioned in my earlier article, the USPTO Office of the Chief Economist has published the Patent Claims Research Dataset, comprising six data files containing individually-parsed claims, claim-level statistics, and document-level statistics for all US patents granted between 1976 and 2014 and US patent applications published between 2001 and 2014.
Having this large data set available caused me to wonder: are patent claims a good predictor of the Art Unit to which an application may be assigned? On the one hand, it seems logical that might be the case. After all, Art Unit assignments are based on technology, and it is generally necessary to refer to technical features of the invention in the patent claims. On the other hand, claim language is often broader and more abstract that the specific field of technology to which the claimed invention may be directed, and the allocation to an Art Unit is, in practice, based upon an initial review of the patent specification as a whole, and not just the claims.
There is, however, only one way to find out whether there is a sufficiently strong correlation between claim language and Art Unit to enable prediction, and that is to conduct some experiments using the available data.
My initial results are promising. By employing some relatively straightforward text processing techniques, I have successfully predicted the Technology Centre to which an application is assigned in just over 70% of cases, the correct group of 10 Art Units in over 40% of cases, and the individual Art Unit in around 24% of cases. This is certainly sufficient to encourage me to persevere with some more sophisticated techniques, to see if it is possible to make further improvements.
It follows that if it were possible to predict, in advance of filing, to which Art Unit a US patent application would likely be assigned, this could go some way towards predicting the prospects of success in examination.
As also mentioned in my earlier article, the USPTO Office of the Chief Economist has published the Patent Claims Research Dataset, comprising six data files containing individually-parsed claims, claim-level statistics, and document-level statistics for all US patents granted between 1976 and 2014 and US patent applications published between 2001 and 2014.
Having this large data set available caused me to wonder: are patent claims a good predictor of the Art Unit to which an application may be assigned? On the one hand, it seems logical that might be the case. After all, Art Unit assignments are based on technology, and it is generally necessary to refer to technical features of the invention in the patent claims. On the other hand, claim language is often broader and more abstract that the specific field of technology to which the claimed invention may be directed, and the allocation to an Art Unit is, in practice, based upon an initial review of the patent specification as a whole, and not just the claims.
There is, however, only one way to find out whether there is a sufficiently strong correlation between claim language and Art Unit to enable prediction, and that is to conduct some experiments using the available data.
My initial results are promising. By employing some relatively straightforward text processing techniques, I have successfully predicted the Technology Centre to which an application is assigned in just over 70% of cases, the correct group of 10 Art Units in over 40% of cases, and the individual Art Unit in around 24% of cases. This is certainly sufficient to encourage me to persevere with some more sophisticated techniques, to see if it is possible to make further improvements.
Tags: Patent analytics