Legal Daily News Feature
The Power of the Pentium (Concept Searching) By Eric Rondeau One of the necessary evils in litigation is document review. Nowadays, the traditional definition of document has come to encompass a broad spectrum of data, from e-mails to Word documents, from text messages to voice mail as well as the flotsam contained on a hard drive. Whether you’re litigating in state or federal court, collection, management and subsequent review of data is getting more complicated. It is also getting more expensive. Not only is there the expense of getting and housing the data/documents, but there is the costly component of review, which in many large defense firms is often their bread and butter when it comes to racking up litigation fees. Often staff or contract attorneys are paid little for the tedious and thankless task while their work is billed to clients with a significant mark up.
07/24/10 However, with the changing economy and clients’ ever growing savviness about attorney billing practices, firms need to confront head on the need for more efficient discovery practices. Data analytics tools have improved by leaps and bounds in the last several years and are often undervalued and underused. They can be, when applied intelligently, an indispensible and very powerful tool. One particular analytical tool, which I’ve used successfully and is offered by a number of legal software developers, is based on conceptual analysis of data. To get into how it works here would not only make your head and my head spin, but would also take up more space than I am allotted for this column. In brief, on the theoretical level, the process of conceptual searching works a lot like T9 or similar programs based on linguistical modeling. It is, as Wikipedia so eloquently puts it: an automated information retrieval method that is used to search electronically stored unstructured text (for example, digital archives, email, scientific literature, etc.) for information that is conceptually similar to the information provided in a search query. In other words, the ideas expressed in the information retrieved in response to a concept search query are relevant to the ideas contained in the text of the query.
It figures out what you are trying to ask or, even better, what the documents say in relationship to one another. No longer are clumsy Boolean type searches necessary. In a Boolean search, you need to anticipate what information is buried in the data. It becomes a game of shooting targets in the dark. Conceptual search tools cluster information that is relative and related to your search parameters and delimiters. Search for ‘’war’’ and you get data conceptually related to ‘’conflict’’, ‘’tank’’, ‘’offensive’’, and ‘’attack’’. The tool can also point out relationships between data that you hadn’t conceived. It makes finding that smoking gun all the more easier. It also catches things a human being wouldn’t necessarily find. On top of that, it can group pools of data into categories to make actual manual reviewing of documents faster and easier. This brings me to my final point. This is not an argument for eliminating the human element. People always have sparks of genius or moments of epiphany where ideas coalesce that lead to the discovery of a new defense or resolution of a particular legal conundrum. These tools are meant to be used in tandem with human brain power. Time saved on the drudgery usually associated with data processing and document review allows for more time spent on formulating arguments and theories related to your data analysis and also save your client money.
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