Search and Math: Stuck in a Rut?
June 23, 2015
I read a paper several years ago. Okay, maybe it was in 2008. You can find the write up here. There is a more recent review of the information in that “Top 10 Algorithms in Data Mining” article here. To make a long story short, most of the search and content processing systems use these tried-and-true methods. Most of them can be implemented using the guidelines in computer science textbooks, and there are plenty of examples to ensure that none of the search and content processing systems fall prey to the Big O issue.
Against this background, I read with interest “The Top 10 Mathematical Achievements of the Last 5ish Years.” I like the specificity of “5ish.” Good math thinking in today’s fuzzy algorithm environment.
The idea is that the write reviews math which sticks up like mountain tops above the cloud layer in the Peruvian Andes. Three of the 10 items snagged my interest, which is skewed by my bias toward search and content processing. Here are the three I highlighted from the 10 in the useful write up:
- The bound gaps between primes. Perhaps the approach will benefit those engaged in making and making cryptography in the next year or so?
- Voevodsky’s Homotopy Type Theory., How can one go wrong with new thoughts on fundamental math.
- Work on The Fundamental Lemma. Gimme some old time group/set religion with potentially useful new handles with which to grab groups.
Now how will search and content processing benefit? For now, not too much. The problem is that innovations in math cannot be applied to most of today’s information processing systems. There are computational considerations, and there are other tasks which need more attention than the plumbing; namely, how can a vendor get the system to output information a licensee can actually use in real life.
I want to remind you, gentle reader, that the reason most search and content processing systems are very much alike has a simple explanation. Most are built using the same 10 components identified in the 2008 paper.
Consider that the next time you plunk down big money for a proprietary system. For most business tasks, open source solutions are substantially similar in core functionality without the hefty price tag for the license, bespoke engineering, and a development cycle more mysterious than the pronouncements of the oracle at Delphi.
Stephen E Arnold, June 23, 2015
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