Shades of CrossZ: Compress Data to Speed Search

September 3, 2015

I have mentioned in my lectures a start up called CrossZ. Before whipping out your smartphone and running a predictive query on the Alphabet GOOG thing, sit tight.

CrossZ hit my radar in 1997. The concept behind the company was to compress extracted chunks of data. The method, as I recall, made use of fractal compression, which was the rage at that time. The queries were converted to fractal tokens. The system then quickly pulled out the needed data and displayed them in human readable form. The approach was called as I recall “QueryObject.” By 2002, the outfit dropped off my radar. The downside of the CrossZ approach was that the compression was asymmetric; that is, slow preparing the fractal chunk but really fast when running a query and extracting the needed data.

Flash forward to Terbium Labs, which has a patent on a method of converting data to tokens or what the firm calls “digital fingerprints.” The system matches patterns and displays high probability matches. Terbium is a high potential outfit. The firm’s methods may be a short cut for some of the Big Data matching tasks some folks in the biology lab have.

For me, the concept of reducing the size of a content chunk and then querying it to achieve faster response time is a good idea.

What do you think I thought when I read “Searching Big Data Faster”? Three notions flitter through my aged mind:

First, the idea is neither new nor revolutionary. Perhaps the MIT implementation is novel? Maybe not?

Second, the main point that “evolution is stingy with good designs” strikes me as a wild and crazy generalization. What about the genome of the octopus, gentle reader?

Third, MIT is darned eager to polish the MIT apple. This is okay as long as the whiz kids take a look at companies which used this method a couple of decades ago.

That is probably not important to anyone but me and to those who came up with the original idea, maybe before CrossZ popped out of Eastern Europe and closed a deal with a large financial services firm years ago.

Stephen E Arnold, September 3, 2015

Written by Stephen E. Arnold · Filed Under Analytics, News, Search, Technology

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Stephen E. Arnold monitors search, content processing, text mining and related topics from his high-tech nerve center in rural Kentucky. He tries to winnow the goose feathers from the giblets. He works with colleagues worldwide to make this Web log useful to those who want to go "beyond search". Contact him at sa [at] arnoldit.com. His Web site with additional information about search is arnoldit.com.