Need Semantic Search: Lucidworks Asserts It Is the Answer by Golly
July 3, 2015
If you read this blog, you know that I comment on semantic technology every month or so. In June I pointed to an article which had been tweeted as “new stuff.” Wrong. Navigate to “Semantic Search Hoohah: Hakia”; you will learn that Hakia is a quiet outfit. Quiet as in no longer on the Web. Maybe gone?
There are other write ups in my free and for fee columns about semantic search. The theme has been consistent. My view is that semantic technology is one component in a modern cybernized system. (To learn about my use of the term cyber, navigate to www.xenky.com/cyberosint.)
I find the promotion of search engine optimization as “semantic” amusing. I find the search service firms’ promotion of their semantic expertise amusing. I find the notion of open source outfits deep in hock to venture capitalists asserting their semantic wizardry amusing.
I don’t know if you are quite as amused as I am. Here’s an easy way to determine your semantic humor score. Navigate to this slideshare link and cruise through the 34 deck presentation made by one of Lucidworks’ search mavens. Lucidworks is a company I have followed since it fired up its jets with Marc Krellenstein on board. Dr. Krellenstein ejected in short order, and the company has consumed many venture dollars with management shifts, repositionings, and the Big Data thing.
We now have Lucidworks in the semantic search sector.
Here’s what I learned from the deck:
- The company has a new logo. I think this is the third or fourth.
- Search is about technology and language. Without Google’s predictive and personalized routines, words are indeed necessary.
- Buzzwords and jargon do not make semantic methods simple. Consider this statement from the deck, “Tokenization plus vector mathematics (TF/IDF) or one of its cousins—“bag of words” – Algorithmic tweaks – enhanced bag of words.” Got that, gentle reader. If not, check out “sausagization.”
- Lucidworks offers a “field cache.” Okay, I am not unfamiliar with caching in order to goose performance, which can be an issue with some open source search systems. But Searchdaimon, an open source search system developed in Norway, runs circles around Lucidworks. My team did the benchmark test of major open source systems. Searchdaimon was the speed champ and had other sector leading characteristics as well.)
- Lucidworks does the ontology thing as well. The tie up of “category nodes” and “evidence nodes” may be one reason the performance goblin noses into the story.
The problem I encountered is that the write up for the slide deck emphasized Fusion as a key component. I have been poking around the “fusion” notion as we put our new study of the Dark Web together. Fusion is a tricky problem and the US government has made fusion a priority. Keep in mind that content is more than text. There are images, videos, geocodes, cryptic tweets in Farsi, and quite a few challenging issues with making content available to a researcher or analyst.
It seems that Lucidworks has cracked a problem which continues to trouble some reasonably sophisticated folks in the content analysis business. Here’s the “evidence” that Lucidworks can do what others cannot:
This diagram shows that after a connector is available, then “pipelines proliferate.” Well, okay.
I thought the goal was to process content objects with low latency, easily, and with semantic value adds. “Lots of stages” and “index pipelines: one way query pipelines: round trip” does not compute for this addled goose.
If the Lucidworks approach makes sense to you go for it. My team and I will stick to here and now tools and open source technology which works without the semantic jargon which is pretty much incidental to the matter. We need to process more than text. CyberOSINT vendors deliver and most use open source search as a utility function. Yep, utility. Not the main event. The failure of semantic search vendors suggests that the buzzword is not the solution to marketing woes. Pop. (That’s a pre fourth of July celebratory ladyfinger.)
Stephen E Arnold, July 3, 2015
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