Micro vs. Macro Information Retrieval

The Probably Irrelevant blog has been quiet for a while, but I was happy to see a new post there by Miles Efron about “micro-IR“. He characterizes micro-IR, as distinct from macro or general IR, as follows:

  1. In ad hoc (text) IR a principal intellectual challenge lies in modeling ‘aboutness.’  In micro-IR settings, the creativity comes into play in posing a useful (and tractable) question to answer.  The engineering comes easily after that.
  2. The constrained nature of micro-IR applications leads to a lightweight articulation of information need.  There is a tight coupling here between task, query, and the unit of retrieval, a dynamic that I think is compelling.  Pushing this a bit farther, we might consider the simple act of choosing to use a particular application from those apps on a user’s palette as part of the information need expression.
  3. The tight coupling of task to data to ‘query’ enables a strong contextual element to inform the interaction.  Context constitutes the foreground of the micro-IR interaction.

He then asks: “is micro-IR something at all?  Is it actually related to IR?” Fernando Diaz answers that “the only difference between micro and macro IR is text.” Jinyoung Kim adds that in micro-IR “the context (searcher goal) is known, with domain-specific notion of relevance (goodness) and similarity measures.”

I hadn’t thought of making this particular distinction, but I like it. While I prefer to think about distinguishing the needs of information seekers–rather than the characteristics of search applications–I would be the first to argue that a well-designed search application caters to particular user needs. Indeed, I think the definition of a good micro-IR application implies that it addresses a highly constrained space of information needs. Just as importantly, micro-IR applications can often assume that their users are highly familiar with the information space the applications address, and thus that those users need less of the basic orienteering support that can be critical for success using macro-IR systems. That said, micro-IR users have (or should have) higher expectations of support for more sophisticated information seeking.

The other day, I speculated about why Google holds back on faceted search. I feel that the distinction between macro- and micro-IR is in the same vein: micro-IR settings (e.g., site search, enterprise search,vertical search) drive needs for more richer interfaces and support for interaction, while macro-IR application developers (e.g., general web search) worry mostly about producing a reasonable answer for the query–and often lead users to micro-IR destinations that offer their own support for information seeking within their constrained domains.

In short, it’s a nice way to think about the IR application space, and it’s increasingly relevant (no pun intended!) as we see a proliferation of micro-IR applications. And it’s great to see activity on the Probably Irrelevant blog after all these months of radio silence!

By Daniel Tunkelang

High-Class Consultant.

7 replies on “Micro vs. Macro Information Retrieval”

Thanks for the shout-out.
I think you’ve hit on several good points that hadn’t occurred to me.

You’re spot on when you say that in the focused search setting that I called call micro-IR high expectations drive the interaction. Searchers expect results that _solve_ a problem. And as you point out, developers can take a degree of user preparedness for granted.

I think it’s also right to note that in many ‘macro’ IR interactions, a search system funnels users towards more focused applications. This is important to keep in mind, lest we draw too firm a line between these modes of search.


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