Interesting post by Michael Martinez from the SEO Theory blog on how “relevance” does and doesn’t relate to the pragmatics of search engine optimization. (I’m not familiar with the term “null relevance” in this context, though— gotta call the Answer Man!)
Oh, here comes relevance again, in the increasingly important graphical context. (And here’s a link to the relevant conference paper by Google researchers.)
(Note: the illustration above of the “graphical relevance debugger” from BigFix is relevant in some ways, but not in others. An illustration of the difficulty of illustrating relevance!)
In case anyone is curious as to what is not considered a fundable topic for internal summer research support by the University of Oklahoma this year, here’s mine:
Opening the Black Box of “Actionable Intelligence”
Abstract:
This proposal offers a new model based on contemporary research in information science that will explore the most critical area of competitive intelligence today: so-called “actionable intelligence.” The project will examine key strategic decisions within the U.S. computer industry as described by 75 of the leading entrepreneurs and executives of the past quarter-century in order to determine what, why, and how “relevant information” becomes “actionable intelligence” within the current high-velocity business environment. This project is also intended as part of an ongoing effort to re-invent relevance research for the new global information environment.
The title of this proposal alludes to a seminal article in library and information science from 40 years ago: “Opening the Black Box of Relevance” by Cuadra and Katter (1967). Their important work began the complex process of unpacking the multidimensional concept of “relevance” (Mizzaro, 1997; Saracevic, 2006) which was originally viewed as a fairly elementary attribute pertaining to a particular piece of information (Goffman, 1964) but which has since been deconstructed over time into a user-oriented construct (Schamber, Eisenberg, and Nilan, 1990) best represented as a continuum (Spink, Greisdorf, and Bateman, 1998) comprised of such components as task relevance (Taylor, Cool, Belkin, and Amadio, 2006), algorithmic relevance (Saracevic, 1975), topic relevance (Janes, 1994), psychological relevance (Harter, 1992), cognitive relevance (Cosijin and Ingwersen, 2000), and situational relevance (Wilson, 1973), among others (Mizzaro, 1998).
The research proposed here will attempt to do the same for the concept of “actionable intelligence.” This term describes particularly relevant and presumably novel information that is likely to precipitate some kind of active response to its import. “Actionable intelligence” has received its greatest notoriety in reference to the events of September 11, 2001 and the alleged discovery of weapons of mass destruction in Iraq and the subsequent initiation of military actions by the United States and its political partners (Hartnett and Stengrim, 2004; Herman, 2002), but it has also been used in reference to the gathering and use of competitive intelligence by business organizations for at least three decades (e.g., Montgomery and Weinberg, 1979). Contemporary management approaches require extensive intelligence gathering to ensure that correct assumptions are being made about the environment and competitor capabilities. Without such intelligence, any actions attempted to develop, maintain, and extend the firm’s key assets and competencies may be flawed and even fail (Powell and Bradford, 2000). This second usage is the one of most interest to the proposed research, as it is closely associated with the learning organization, a crucial concept in knowledge management (Choo, 1998).
Competitive intelligence stems from an organizational paradigm that centers on group decision-making focused on so-called “key intelligence topic” that both inform and are informed by an ongoing series of items of information found by a variety of means (Fahey, 2007; Francis and Herring, 1999; Herring, 1999). Rather than concentrating on an organized collection of information sources as in traditional library reference settings, the emphasis is on collecting highly relevant information that may or may not already exist in any organized form. This also means that a much wider net is cast: the information sought may include such diverse sources as so-called “open source intelligence” (unpublished and published documents from a wide variety of sources), “human intelligence” (the elicitation of oral information), and “tech-int intelligence” (the analysis of data from a variety of technologies, especially geospatial ones).
Competitive intelligence also posits a strategic user group within the organizational setting. Competitive intelligence revolves around the so-called “intelligence cycle,” in which the one group specifies the general area in which intelligence is to be collected, and the other group is then responsible for collecting, evaluating, and analyzing relevant information that is then delivered as a potential decision-making input to the strategic end-users (Antia and Hesford, 2007). While competitive analyst cognition (Herbert, 2006; Heuer, 1999), managerial cognition (Barr, 1998; Clark and Montgomery, 1999), the difficulties the two groups encounter in attempting communication (Bernhardt, 1999), and various aspects of the entire process (Powell and Bradford, 2000; Thomas, Clark and Gioia, 1993) have all been studied, precisely what makes relevant information into “actionable intelligence” has received little attention. This research will attempt to address this omission.
(As may be obvious, since I’ve already started on this project, it’s a bit late not to continue on with it. Guess you can call me “Oklahoma tough” now!
One thing I always enjoyed at the Press was seeing the new book jacket designs being worked on, so this particularly cool application of color theory in progress caught my eye.
And it’s relevance-related too!
Oh, geographical relevance! Darn, I wish I’d thought of that! (Come to think of it, why didn’t anyone else? Now that it seems so obvious…..)
Contemplating such things as the conduit metaphor, cognitive mapping, concept maps, knowledge mapping, and the ongoing project of data mining my own memory for useful items for both 5033 and 5553 this semester, I happened to recall this interesting essay by Nicholas Burbules, who points out:
“There are questions one knows how to answer.
There are questions one does not know how to answer.
There are questions one does not know how to ask.
There are questions that cannot be answered.”
Just so. And how might all that relate to my ongoing interest in “relevance work” in its many manifestations? Hmm……
Still pondering the many facets of relevance, and came across this notion from the SEO Theory blog that, regardless of whatever the future of the so-called “semantic web” may be, it’s likely that what we might well consider “next-generation relevance” will involve household appliances. Love the implications for defining relevance criteria. Perhaps Cuadra’s and Katter’s “black box of relevance” should be renamed the “icebox of relevance”?
(It’s also quite interesting that so-called “SEO theory” defines itself without any reference to much previous relevance-related IR research: talk about Swanson’s concept of “undiscovered public knowledge”!)
and things that I wish I’d written, here is Tefko Saracevic’s magisterial review of relevance. I especially like this from page 22: “For a fleeting decade, relevance had its Camelot. It was in Syracuse. From about the mid-1980s until about the mid-1990s, a series of doctoral dissertations at the School of Informqtion Studies, Syracuse University, addressed various aspects of relevance, reflecting a vigorous research environment under the guiding spirit of Robert Taylor and Jeffrey Katzer.” Nothing like missing Camelot… twice, since I was there both before and after this decade. No wonder I find myself still fixating on relevance!
Memedonkey, in the 5433 class, has just steered me towards Malcolm Gladwell’s “The Social Life of Paper,” which I’d somehow missed back in 2002. All I can say is, thank heavens that relevance is multi-dimensional and gives us these second chances!
Very interesting preliminary findings from Search Engine Land on possible differences in how Westerners and Chinese view (and value) presentation of Internet search results. If, in fact, the Chinese prefer “hot and noisy” in their Internet search engines (which is suggested as one of the reasons as to why they choose Baidu over Google), does the same hold true for relevance in their OPACs and other library applications? And, if so, how is it possible that this research isn’t being done and published in journals like JASIST, I wonder?
