Lex Machina: IP Litigation and analytics
From the about page:
Every day, Lex Machina’s crawler extracts data and documents from PACER, all 94 District Court sites, ITC’s EDIS site and the PTO site.
The crawler automatically captures every docket event and downloads key District Court case documents and every ITC document. It converts the documents by optical character recognition (OCR) to searchable text and stores each one as a PDF file.
When the crawler encounters an asserted or cited patent, it fetches information about that patent from the PTO site.
Next, the crawler invokes Lex Machina’s state-of-the-art natural language processing (NLP) technology, which includes Lexpressions™, a proprietary legal text classification engine. The NLP technology classifies cases and dockets and resolves entity names. Attorney review of docket and case classification, patents and outcomes ensures high-quality data. The structured text indexer then orders all the data and stores it for search.
Lex Machina’s web-based application enables users to run search queries that deliver easy access to the relevant docket entries and documents. It also generates lists that can be downloaded as PDF files or spreadsheet-ready CSV files.
Finally, the system generates a daily patent litigation update email, which provides links to all new patent cases and filings.
Lex Machina does not:
- Index the World Wide Web
- Index legal cases around the world in every language
- Index all legal cases in the United States
- Index all state courts in the United States
- Index all federal court cases in the United States
Instead, Lex Machina chose a finite legal domain, patents, that has a finite vocabulary and range of data sources.
Working in that finite domain, Lex Machina has produced a high quality data product of interest to legal professions and lay persons alike.
I intend to leave conquering world hunger, ignorance and poor color coordination of clothing to Bill Gates.
You?
I first saw this at Natural Language Processing in patent litigation: Lex Machina by Junling Hu.