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Nothing is “Miscellaneous” October 17, 2009

Posted by Andre Vellino in Classification, Collaborative filtering, Information retrieval, Recommender service.
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everything-is-miscellaneousI think I now understand why David Weinberger’s book “Everything is Miscellaneous” is so provocative and sometimes enraging.  It often sounds like he’s claiming that there is no point at all in classifing / categorizing information.  No matter what you do, you’re going to get the category “wrong” because there is no such thing as a “right” category. Ergo, don’t even try – everything belongs in the category “Misc”.

I think Weinberger’s emperor has no clothes – in fact, he is asserting that nothing is “Miscellanous”. Everything belongs to some category for someone, it’s just that it may not be the same category for everyone. A banana is likely to be a fruit for most people, but also a weapon for John Cleese.  The point is: a banana is always a kind of something in every context.

So isn’t there is a middle ground between banishing the Dewey decimal system (or indeed any other library classification system) and dumping every digital object into an undifferentiated pile.  Indeed, there’s a lot to be said for a thoroughly well-understood standard, albeit a dated and even a bad, system of classification: at the very least, it is predictable.  If you know how the meta-data was generated (e.g. call-number, subject category, keywords), for a given item, you’ll be better able to retrieve it.

Furthermore, I expect there are some unforseen problems with the democratization of knowledge generated by social tagging and recommender systems.  Who’s doing the tagging?  Who’s doing the bookmarking? High school students?

This is of particular concern to me in the context of scholarly articles. Are the numbers of co-downloads in a digital library primarily due to professors’ undergraduate course syllabi?  Would professors’ syllabi be influenced by scholarly recommender systems?  I expect that the recommender-effect studied in Daniel Fleder’s “Blockbuster Culture’s Next Rise or Fall: The Impact of Recommender Systems on Sales Diversity” and which shows that recommenders decrease aggregate diversity would be an especially accute problem when sources of co-download behaviour are (relatively) few (e.g. professors’ course syllabi).

Conclusion? I think it matters what population you are drawing from for your metadata – be it social tagging or collaborative filtering recommendations.  There is a point in relying on experts and big thinkers.  They are more knowledgeable and credible than even the collective intelligence of the masses.

Comments»

1. Daniel Lemire - October 19, 2009

I think there is a difference between classifying books on shelves, and retrieving digital documents on a laptop.

The Dewey system is a workaround for our inability to index physical objects in rich ways. I can’t very well do full text search on physical books, can I?

In the digital age, we no longer need Dewey, except maybe at the public library… until we move to e-books… which should happen with a decade or so.

2. Andre Vellino - October 19, 2009

Yes – Weinberger makes that point forcefully. Systems like Dewey were designed for labeling physical things that are located in a building. In the digital world there are multiple ways of tagging / annotating / labeling that permits a plurality of mechanisms for accessing the same object. Which *is* definitely an advantage of the digital world. Severely flawed systems like Dewey can be much more easily replaced – simultaneously – by other classification systems.

I think my point is – some classification systems are better than others.
Social tagging and recommender systems have their Achilles heel namely: how do we trust them?

My hunch is that even when e-books replace physical books in a library, it will still be worth while to get a human brain to verify whether a software-based keyword extractor / subject classification system did a reasonable job. I think I’m jaded about the endless unfulfilled promises that AI will replace humans (adequately).


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