IDOL Is Back and with NLP
December 11, 2016
I must admit that I am confused. Hewlett Packard bought Autonomy, wrote off billions, and seemed to sell the Autonomy software (IDOL and DRE) to an outfit in England. Oh, HPE, the part of the Sillycon Valley icon, which sells “enterprise” products and services owns part of the UK outfit which owns Autonomy. Got that? I am not sure I have the intricacies of this stunning series of management moves straight in my addled goose brain.
Close enough for horseshoes, however.
I read what looks like a content marketing flufferoo called “HPE Boosts IDOL Data Analytics Engine with Natural Language Processing Tools.”
I thought that IDOL had NLP functions, but obviously I am wildly off base. To get my view of the Autonomy IDOL system, check out the free analysis at this link. (Nota bene: I have done a tiny bit of work for Autonomy and have had to wrestle with the system when I labored with the system as a contractor when I worked on US government projects. I know that this is no substitute for the whizzy analysis included in the aforementioned write up. But, hey, it is what it is.)
The write up states in reasonably clear marketing lingo:
HPE has added natural language processing capabilities to its HPE IDOL data analytics engine, which could improve how humans interact with computers and data, the company announced Tuesday. By using machine learning technology, HPE IDOL will be able to improve the context around data insights, the company said.
A minor point: IDOL is based on machine learning processes. That’s the guts of the black box comprising the Bayesian, LaPlacian, and Markovian methods in the guts of the Digital Reasoning Engine which underpins the Integrated Data Operating Layer of the Autonomy system.
Here’s the killer statement:
… the company [I presume this outfit is Hewlett Packard Enterprise and not MicroFocus] has introduced HPE Natural Language Question Answering to its IDOL platform to help solve the problem. According to the release, the technology seeks to determine the original intent of the question and then “provides an answer or initiates an action drawing from an organization’s own structured and unstructured data assets in addition to available public data sources to provide actionable, trusted answers and business critical responses.
I love the actionable, trusted bit. Autonomy’s core approach is based on probabilities. Trust is okay, but it is helpful to understand that probabilities are — well — probable. The notion of “trusted answers” is a quaint one to those who drink deep from the statistical springs of data.
I highlighted this quotation, presumably from the wizards at HPE:
“IDOL Natural Language Question Answering is the industry’s first comprehensive approach to delivering enterprise class answers,” Sean Blanchflower, vice president of engineering for big data platforms at HPE, said in the release. “Designed to meet the demanding needs of data-driven enterprises, this new, language-independent capability can enhance applications with machine learning powered natural language exchange.”
My hunch is that HPE or MicroFocus or an elf has wrapped a query system around the IDOL technology. The write up does not provide too many juicy details about the plumbing. I did note these features, however:
- An IDOL Answer Bank. Ah, ha. Ask Jeeves style canned questions. There is no better way to extract information than the use of carefully crafted queries. None of the variable, real life stuff that system users throw at search and retrieval systems. My experience is that maintaining canned queries can become a bit tedious and also expensive.
- IDOL Fact Bank. Ah, ha. A query that processes content to present “factoids.” Much better than a laundry list of results. What happens when the source data return factoids which are [a] not current, [b] not accurate, or [c] without context? Hey, don’t worry about the details. Take your facts and decide, folks.
- IDOL Passage Extract. Ah, ha. A snippet or key words in context! Not exactly new, but a time proven way to provide some context to the factoid. Now wasn’t that an IDOL function in 2001? Guess not.
- IDOL Answer Server. Ah, ha. A Google style wrapper; that is, leave the plumbing alone and provide a modernized paint job.
If you match these breakthroughs with the diagram in the HP IDOL write up’s diagrams, you will note that these capabilities appear in the IDOL/DRE system diagram and features.
What’s important in this content marketing piece. The write up provides a takeaway section to help out those who are unaware of the history of IDOL, which dates from the late 1990s. Here you go. Revel in new features, enjoy NLP, and recognize that HPE is competing with IBM Watson.
There you go. Factual content in action. Isn’t modern technology analysis satisfying? IBM Watson, your play.
Stephen E Arnold, December 11, 2017
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2 Responses to “IDOL Is Back and with NLP”
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Spot on Mr. Arnold. Just spot-on. My idea on Watson is that they are not delivering data visualization as well as they could easily do with an acquisition of any umber of break through data-cultivation engines.
Pardon the typo. ‘Any number…’