Legal Research

Nomus: A New Canadian Caselaw Search Engine

By Simon Fodden

Here’s a turn-up for the books: there’s a new entry in the Canadian legal search engine market. CanLII notwithstanding, Kent Mewhort, a McGill law student and experienced software engineer, has launched Nomus, a free search engine for Canadian legal decisions.

This is no Google-based amateur effort, but rather a serious tool running with at least one interesting algorithm and one valuable additional feature. I’ve had a small exchange of emails with Mr. Mewhort, and some of the material in this post comes from that.

First the scope: the database is drawn from publicly available, i.e. governmental, sites publishing court decisions and at the moment comprises only decisions from the following courts forward from the dates set out:

SCC (1876); FCA (1988); FC (1990); TCC (1996); ABQB (2003); ABCA (1998); ABPC (1998); BCCA (1990); BCSC (1990); NBCA (2008); NSCA (1995); NSSC (1999); NSPC (2000); ONCA (1999); PESC (2000); PECA (2009); QCCS (2001); QCCQ (2001); QCCA (1987); YKCA (2001); YKSC (2001); YKSM (2002)

I imagine that it will continue to expand the number of courts in time as they put their decisions online directly.

The principal notion behind Nomus is the ability to search in an unstructured way using terms or phrases, although search operators are indeed supported, including the helpful “term boost” that weights results in favour of a particular configuration of your search terms. Results, which can be filtered in various ways, are delivered according to the following relevancy considerations, as described in the FAQ:

Term frequency, a measurement of how often a search term is found in a particular document;
Term uniqueness, a measure of how specific or unique a search term is;
Term proximity, a measure of how close search terms are to one another in a particular document; and
Term precedential importance, a measure created from an analysis of the citation networks between cases. This measurement includes a consideration of how frequently a particular judgment has been cited in association with a search term, the authority of the citing courts, and how recently the citing judgments were delivered.

This last is interesting. As explained by Mr. Mewhort:

Let us consider the relevancy of R. v. Grant, 2009 SCC 32. In R. v. Wong, 2010 BCCA 160, the B.C. Court of Appeal mentions that “[a]s a result of the decisions in Grant and Harrison, trial courts have been directed to take a view of all relevant circumstances in making a decision about admissibility of evidence under s. 24(2) of the Charter.” This will boost Grant (and Harrison) on any search for ‘admissibility of evidence’ or for ‘Charter s. 24(2)’ because these terms are mentioned in a context that refers to Grant.

The interesting feature I mentioned at the outset is the “Case Box,” which allows you to drag representations of search results onto a graphic, where the information is stored until you decide to download, email or print the results.

I asked Mr. Mewhort why he felt that this was a worthwhile enterprise, given the existence of CaLII. Essentially, his view is that the Nomus algorithm gives better results for the way in which most people search, which, he believes, is with unstructured keywords; and he points to the citation-in-association feature just mentioned:

With the primary goal of result relevancy, the Nomus search engine uses several sophisticated factors in search relevancy calculations that, to my knowledge, are not currently used by other legal search engines. Foremost, the search engine analyzes how often a particular judgment is cited in association with a particular topic being searched for.

For me this is still a bit of a head scratcher: the engineering is highly sophisticated but the coverage is so spotty as to make it of small use in many cases; certainly someone in Ontario, for example, is unlikely to get much joy from it, given the absence of trial court judgments. I see this as akin to a testbed, where algorithms can be developed and refined that might prove useful to CanLII, or, I suppose, the commercial databases. Which raises another matter, that of money. As the last line of the FAQ says, “For the time being, Nomus is entirely free.” Mewhort is seeking donations to support this service, a difficult quest at any time and no joke in the present climate.

I’ve not run comparison searches with Nomus and CanLII — but I’m sure that Slaw readers will do that and report to us.

Full post as published by Slaw.ca on April 06, 2010 (boomark / email).