NetBase and Content Intelligence
April 30, 2009
Vertical search is alive and well. Technology Review described NetBase’s Content Intelligence here. The story, written by Erica Naone, was “A Smarter Search for What Ails You”. Ms. Naone wrote:
organizes searchable content by analyzing sentence structure in a novel way. The company created a demonstration of the platform that searches through health-related information. When a user enters the name of a disease, he or she is most interested in common causes, symptoms, and treatments, and in finding doctors who specialize in treating it, says Netbase CEO and cofounder Jonathan Spier. So the company’s new software doesn’t simply return a list of documents that reference the disease, as most search engines would. Instead, it presents the user with answers to common questions. For example, it shows a list of treatments and excerpts from documents that discuss those treatments. The Content Intelligence platform is not intended as a stand-alone search engine, Spier explains. Instead, Netbase hopes to sell it to companies that want to enhance the quality of their results.
NetBase (formerly Accelovation) has developed a natural language processing system.Ms. Naone reported:
NetBase’s software focuses on recognizing phrases that describe the connections between important words. For example, when the system looks for treatments, it might search for phrases such as “reduce the risk of” instead of the name of a particular drug. Tellefson notes that this isn’t a matter of simply listing instances of this phrase, rather catching phrases with an equivalent meaning. Netbase’s system uses these phrases to understand the relationship between parts of the sentence.
At this point in the write up, I heard echoes of other vendors with NLP, semantics, bound phrase identification, etc. Elsevier has embraced the system for its illumin8 service. You can obtain more information about this Elsevier service here. Illumin8 asked me, “What if you could become an expert in any topic in a few minutes?” Wow!
The NetBase explanation of content intelligence is:
… understanding the actual “meaning” of sentences independent of custom lexicons. It is designed to handle myriads of syntactical sentence structures – even ungrammatical ones – and convert them to logical form. Content Intelligence creates structured semantic indexes from massive volumes of content (billions of web-pages and documents) used to power question-and-answer type of search experiences.
NetBase asserts:
Because NetBase doesn’t rely on custom taxonomies, manual annotations or coding, the solutions are fully automated, massively scalable and able to be rolled-out in weeks with a minimal amount of effort. NetBase’s semantic index is easy to keep up-to-date since no human editing or updates to controlled vocabulary are needed to capture and index new information – even when it includes new technical terms.
Let me offer several observations:
- The application of NLP to content is not new and it imposes some computational burdens on the search system. To minimize those loads, NLP is often constrained to content that contains a restricted terminology; for example, medicine, engineering, etc. Even with a narrow focus, NLP remains interesting.
- “Loose” NLP can squirm around some of the brute force challenges, but it is not yet clear if NLP methods are ready for center stage. Sophisticated content processing often works best out of sight, delivering to the user delightful, useful ways to obtain needed information.
- A number of NLP systems are available today; for example, Hakia. Microsoft snapped up PowerSet. One can argue that some of the Inxight technology acquired first by Business Objects then by the software giant SAP are NLP systems. To my knowledge, none of these has scored a hat trick in revenue, customer uptake, and high volume content processing.
You can get more information about NetBase here. You can find demonstrations and screenshots. A good place to start is here. According to TechCrunch:
NetBase has been around for a while. Originally called Accelovation, it has raised $9 million in two rounds of venture funding over the past four years, has 30 employees…
In my files, I had noted that the funding sources included Altos Ventures and ThomVest, but these data may be stale or just plain wrong. I don’t have enough information about Netbase to offer substantive comments. NLP requires significant computing horsepower. I need to know more about the plumbing. Technology Review provided the sizzle. Now we need to know about the cow from which the prime rib comes.
Stephen Arnold, April 30, 2009
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