New Discussion: Bommarito on Hands-on Examples of Legal Search

Michael J. Bommarito II of Computational Legal Studies has started a discussion entitled Hands-on Examples of Legal Search, in the LinkedIn group of the International Association for Artificial Intelligence and Law (IAAIL).

The examples are Mr. Bommarito’s recent work describing cloud-based approaches to legal information retrieval and eDiscovery using AWS CloudSearch (here, here, and here), and information retrieval of statutes using Lucene.

For more information, please see the complete post.

Bommarito on AWS CloudSearch for eDiscovery: Generating AWS CloudSearch SDF for Emails

Michael J. Bommarito II of Computational Legal Studies has posted Generating AWS CloudSearch SDF for Emails, and “Google” for subpoenaed emails: AWS CloudSearch for eDiscovery, on his blog.

In these posts, Mr. Bommarito proposes using AWS CloudSearch for ediscovery, and provides a worked example, which he describes as follows:

I thought I’d share a proof-of-concept email parser based on the Enron email dataset. The Python script below takes a directory of RFC822 email messages and returns an AWS CloudSearch JSON SDF with fields from the Date, From, To, Subject, and Body fields of the email. There is no special handling for attachments or encoding in this example, but it can be used to populate a CloudSearch domain from the Enron emails. Sample usage below, as well as the output sample here. [...]

For more information, including source code, please see the complete posts: Generating AWS CloudSearch SDF for Emails, and “Google” for subpoenaed emails: AWS CloudSearch for eDiscovery.

Kang et al. on Making Sense of Archived E-mail: Exploring the Enron Collection with NetLens

Dr. Hyunmo Kang of the Carnegie Mellon University Department of Computer Science, and colleagues from the University of Maryland College Park UMIACS Human-Computer Interaction Laboratory, have published Making Sense of Archived E-mail: Exploring the Enron Collection with NetLens, forthcoming in Journal of the American Society for Information Science and Technology (JASIST). Here is the abstract:

“Informal communications media pose new challenges for information-systems design, but the nature of informal interaction offers new opportunities as well. This paper describes NetLens-E-mail, a system designed to support exploration of the content-actor network in large e-mail collections. Unique features of NetLens-E-mail include close coupling of orientation, specification, restriction, and expansion, and introduction and incorporation of a novel capability for iterative projection between content and actor networks within the same collection. Scenarios are presented to illustrate the intended employment of NetLens-E-mail, and design walkthroughs with two domain experts provide an initial basis for assessment of the suitability of the design by scholars and analysts.”

This paper may be of interest to legal informatics researchers for several reasons. First, the data set studied in the paper is a collection of law-related documents: email messages disclosed during the U.S. Federal Energy Regulatory Commission (FERC)‘s legal investigation into Enron. See, e.g., the explanation at the data set’s homepage at Carnegie Mellon ; Bryan Klimt & Yiming Yang, Introducing the Enron Corpus (2004); Federal Energy Regulatory Commission, Press Release, Western Energy Markets: Major Issuance on March 26, 2003 – Information Released in Investigation (26 March 2003).

Second, I believe that this data set has been among those studied by participants in the TREC (Text Retrieval Conference) Legal Track, an important legal information retrieval research project.

Third, the findings of this paper may be relevant to a number of legal informatics applications, particularly those involving electronic discovery.

Fourth, the paper may be of interest to researchers who use social informatics methods, including social network theory, to study legal information and communication.