Natural language processing (NLP)
Analysis of natural language processing (NLP) technologies.
SAP’s “search” strategy isn’t about search
I caught up with Dennis Moore today to talk about SAP’s search strategy. And the biggest thing I learned was – it’s not about the search. Rather, it’s about a general interface, of which search and natural language just happen to be major parts.
Dennis didn’t actually give me a lot of details, at least not ones he’s eager to see published at this time. That said, SAP has long had a bare-bones search engine TREX. (TREX was also adapted to create the columnar relational data manager BI Accelerator.) But we didn’t talk about TREX enhancements at all, and I’m guessing there haven’t really been many. Rather, SAP’s focus seems to be on:
A. Finding business objects.
B. Helping users do things with them.
| Categories: BI integration, Enterprise search, Language recognition, Natural language processing (NLP), SAP, Search engines | 2 Comments |
InQuira’s and Mercado’s approaches to structured search
InQuira and Mercado both have broadened their marketing pitches beyond their traditional specialties of structured search for e-commerce. Even so, it’s well worth talking about those search technologies, which offer features and precision that you just don’t get from generic search engines. There’s a lot going on in these rather cool products.
In broad outline, Mercado and InQuira each combine three basic search approaches:
- Generic text indexing.
- Augmentation via an ontology.
- A rules engine that helps the site owner determine which results and responses are shown under various circumstances.
Of the two, InQuira seems to have the more sophisticated ontology. Indeed, the not-wholly-absurd claim is that InQuira does natural-language processing (NLP). Both vendors incorporate user information in deciding which search results to show, in ways that may be harbingers of what generic search engines like Google and Yahoo will do down the road. Read more
| Categories: InQuira, Mercado, Natural language processing (NLP), Ontologies, Search engines, Structured search | 2 Comments |
Why the BI vendors are integrating with Google OneBox
I’m hearing the same thing from multiple BI vendors, with SAS being the most recent and freshest in my mind — customers want them to “integrate” with Google OneBox. Why Google rather than a better enterprise search technology, such as FAST’s? So far as I’ve figured out, these are the reasons, in no particular order:
- Price.
- Ease of installation (real or imagined).
- The familiar Google brand name.
- The familiar Google UI.
- Google OneBox’s ability to search relational records, reports, etc. along with more tradtional record types.
The last point, I think, is the most interesting. Lots of people think text search is and/or should be the dominant UI of the future. Now, I’ve been a big fan of natural language command line interfaces ever since the days of Intellect and Lotus HAL. But judging by the market success of those products — or for that matter of voice command/control — I was in a very small minority. Maybe the even simpler search interface — words jumbled together without grammatical structure — will win out instead.
Who knows? Progress is a funny thing. Maybe the ultimate UI will be one that responds well to grunts, hand gestures, and stick-figure drawings. We could call it NeanderHAL, but that would wrong …
| Categories: BI integration, Enterprise search, FAST, Google, Natural language processing (NLP), SAS, Search engines | 1 Comment |
That great linguist, Groucho Marx, and other stories
If you’re reading this blog, you’re probably familiar with a saying that illustrates some of the basic challenges of disambiguation:
Time flies like an arrow. Fruit flies like a banana.
But did you know who said it first? I didn’t until recently. Read more