Tools for parsing and extracting information from USPTO patents
In 2012, I published a paper on the impact of misspellings in patents. Here is the abstract:
The search in patent databases is a risky business compared to the search in other domains. A single document that is relevant but overlooked during a patent search can turn into an expensive proposition. While recent research engages in specialized mod- els and algorithms to improve the effectiveness of patent retrieval, we bring another aspect into focus: the detection and exploitation of patent inconsistencies. In particular, we analyze spelling errors in the assignee field of patents granted by the United States Patent & Trademark Office. We introduce technology in order to improve retrieval effectiveness despite the presence of typographical ambiguities. In this regard, we (1) quantify spelling errors in terms of edit distance and phonological dissimilarity and (2) render error detection as a learning problem that combines word dissimilarities with patent meta-features. For the task of finding all patents of a company, our approach improves recall from 96.7% (when using a state-of-the-art patent search engine) to 99.5%, while precision is compromised by only 3.7%.
You can read the full paper here.
Processing the XML patent data set wasn't straightforward, because some files were corrupt, and the SGML changed from year to year. Please find in this repository some parsers written in Python. Beware, that I just duplicated the code for different years or use-cases.
Refer to the usage information via ``--help''.
Dennis Hoppe
Copyright 2014 Dennis Hoppe.
