Monday, December 16, 2013

Ye Olde Artisanal Information Retrieval Algorithm Shoppe

From Cornell Law School's  VoxPopuLII blog:

Everything is Editorial: Why Algorithms are Hand-Made, Human, and Not Just for Search Anymore
Artisanal Algorithms
Down here in Durham, NC, we have artisanal everything: bread, cheese, pizza, peanut butter, and of course coffee, coffee, and more coffee. It’s great—fantastic food and coffee, that is, and there is no doubt some psychological kick from knowing that it’s been made carefully by skilled craftspeople for my enjoyment. The old ways are better, at least until they’re co-opted by major multinational corporations.

Aside from making you either hungry or jealous, or perhaps both, why am I talking about fancy foodstuffs on a blog about legal information? It’s because I’d like to argue that algorithms are not computerized, unknowable, mysterious things—they are produced by people, often painstakingly, with a great deal of care. Food metaphors abound, helpfully I think. Algorithms are the “special sauce” of many online research services. They are sets of instructions to be followed and completed, leading to a final product, just like a recipe. Above all, they are the stuff of life for the research systems of the near future.
Human Mediation Never Went Away
When we talk about algorithms in the research community, we are generally talking about search or information retrieval (IR) algorithms. A recent and fascinating VoxPopuLII post by Qiang Lu and Jack Conrad, “Next Generation Legal Search – It’s Already Here,” discusses how these algorithms have become more complicated by considering factors beyond document-based, topical relevance. But I’d like to step back for a moment and head into the past for a bit to talk about the beginnings of search, and the framework that we have viewed it within for the past half-century.

Many early information-retrieval systems worked like this: a researcher would come to you, the information professional, with an information need, that vague and negotiable idea which you would try to reduce to a single question or set of questions. With your understanding of Boolean search techniques and your knowledge of how the document corpus you were searching was indexed, you would then craft a search for the computer to run. Several hours later, when the search was finished, you would be presented with a list of results, sometimes ranked in order of relevance and limited in size because of a lack of computing power.

Presumably you would then share these results with the researcher, or perhaps just turn over the relevant documents and send him on his way. In the academic literature, this was called “delegated search,” and it formed the background for the most influential information retrieval studies and research projects for many years—the Cranfield Experiments. See also “On the History of Evaluation in IR” by Stephen Robertson (2008)....MORE
HT: naked capitalism