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The Next-Generation of Business Intelligence

Semantic Intelligence

Business Intelligence at Cloud Expo

Most people think of traditional business intelligence (BI) as a collection of business-critical information from inside the enterprise.

However, consumer comments, independent reviews, and market reports online are crucial pieces of information coming from the outside that infinitely affect any organization.

Applications, blogs, social networks, and forums where content creation, sharing, and understanding takes place should be part of business intelligence. Locating and analyzing this unstructured data can only be carried out with a different kind of business intelligence solution - one we call semantic intelligence.

What Is Semantic Intelligence?
Semantic intelligence provides early identification and analysis of consumer sentiment, purchasing trends, market deals, and competitive information - and uncovers this data not only from within a organization's network, but also from the most unstructured corners of the Web. You may be thinking that a normal Google search can uncover any Web-based information, but unlike simple keyword search, semantic intelligence uncovers the meaning the words express, in their proper context, no matter the number (singular or plural), gender (masculine or feminine), verb tense (past, present, or future), or mode (indicative or imperative).

For example, say you're a chef and you're looking for details on how to make soup with healthier ingredients, so, you keyword search "apple stock." Try it right now - you'll get dozens upon dozens of pages about Apple, the company. If you try to narrow the search and type, "apple stock and cook," you will still get hundreds of erroneous search results about Tim Cook and Apple, the company.

Semantic intelligence incorporates morphological, logical, grammatical, and natural language analysis that translates into higher precision and recall when searching for information. By providing information in the requested context and form, semantic intelligence helps organizations strategize, analyze, and make predictions because you're getting the correct data - and in these economic times, having the right foresight can save a business.

There's real business value in incorporating semantic intelligence with business intelligence. Including unstructured data provides a more complete corporate picture. Semantic intelligence extracts knowledge from these sources and when combined with BI, businesses receive knowledge from structured and unstructured modalities, which will eventually be a requirement as we move into the next phase of the Web.

Moving into Web 3.0
In the early years of the Web - Web 1.0 - content was only read. Web 1.0 treated words like checkmarks - a series of letters in a certain order from a search query matched to a series of letters in the same order on a page. The underlying meaning of the word, the context in which the word is used, the word's relationship to other words around it weren't considered because there wasn't any user feedback in the equation. As business owners and content producers realized they could reach customers and get feedback from the other end of the world and back in a short amount of time, the content, the way the content was consumed, and the interaction evolved. As such, the Web 2.0 movement was born.

Web 2.0, in its most basic definition, is where the content consumers are also the content producers. As the Web became better designed for immediate interaction, consumers took advantage by socializing, sharing comments, and making purchases. Web 2.0 is an environment for content personalization and expression; except Web 2.0 wasn't designed to locate opinions or knowledge as intended by those content producers.

Web 3.0 is becoming the age of semantics. It's the evolution of the Web where the gap between computing and human understanding is narrowing, and the information and content created by users has more "meaning." It lets the individual find, assemble, and consume only those parts of the Internet that help with one's current task. Web 3.0 works for the user rather than the consumer having to work the Web to get anything useful from it.

Where this semantic-based Web 3.0 world will help businesses (not just consumers) is:

  • Customers' text or e-mail requests to the help desk are immediately understood and filtered to the correct expert for immediate response - from anywhere.
  • Typing in a search term and getting accurate, relevant results, even when the search term has multiple meanings - and having those search results include online ads, comments, Twitter posts, reports, and other unstructured data.
  • Document analysis, categorization, and filing for meetings, product development purposes, auditing, etc.
  • When searching where to place an ad online, getting a list of locations where the ad should be placed due to socio-cultural trends and proper context, not just keyword prevalence.
  • Identifying competitive data, potential crisis areas, and strategic information from internal documents and the World Wide Web.

As semantic intelligence becomes more widely adopted and the natural language processing/human understanding of the Web increases, Web 3.0 will be a reality, not just a buzzword. In Web 3.0, content consumers will continue to double as content producers, and the information will become more valuable to the enterprise. With semantic intelligence added to the fray, the retrieval of that information will be as easy as finding a pizza place in New York City.

Conclusion
The Web will continue to evolve and user-generated content will grow more and more important to business decision-making. The intelligence needed to keep an organization profitable and relevant will filter in from the outside - straight from the mouths of users, competitors, market researchers, and more. Semantic intelligence is the only way to get full use of this data and help your organization evolve. Semantic intelligence is becoming the catalyst for Web 3.0 - helping businesses identify and process data just like - if not better - than a human can comprehend. It's the next evolution of business intelligence. Having the unstructured and structured data analysis will help organizations thrive and obtain the knowledge they need to keep growing their business in the Web 3.0 world.

More Stories By Brooke Aker

Brooke Aker is the CEO of Expert System USA, a leading semantic technology firm. He is a long-standing speaker and writer in the areas of Competitive Intelligence, Knowledge Management and Predictive Analytics. Brooke is a serial entrepreneur having formed both Acuity Software and Cipher Systems, and was a member of the Intelligence practice at The Futures Group/Deloitte Consulting. He wrote the Competitive Intelligence Magazine column entitled "100 Ways to Beat Your Competition." Brooke earned a MA in economics from Boston University and a BA in economics from the University of Vermont.

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Most Recent Comments
Mark Montgomery 01/26/10 06:08:00 PM EST

Well, having seen really good science and technology terms ruined by all manner of excessive prostitution, I didn't expect any difference with semantics. Maybe the economy has helped a bit keep the buzz down.

It's a legit term for embedded meaning in digital files as far as I am concerned, and I think BI works fine for using the analytics for that purpose. The herd has been trained well to accept BI.

It's not the only purpose for the broad term, however. Semantic enterprise to me allows for automated and semi-automated transactions we call descriptive wrappers about the contents of the digital files. Importantly, our system design is tailored to the specific org -- something that has been missing in enterprise software -- adaptability that leads to differentiation.

Semantic intel works for me more broadly -- across say life sciences cluster, whereas BI would be company specific. In our case the QIQO would be tailored to collect intel differently for different purposes and missions. That's how it should be. It only becomes confusing when people take their eye off the mission, or reason for being. .02- MM

Brooke_Aker 03/30/09 11:23:14 AM EDT

Thanks Seth for your comments on my article. You are right of course about the use of 'Semantic Intelligence'. We only choose to use this term to try to help distinguish it from the long standing notion of Business Intelligence as data mining. IBM coined the term long ago and has spent millions promoting this to the point it is lodged pretty firmly in the minds of those who are in the field one way or another.

On the Google front while there seems to be progress as you point out why, for the life of me, don't they do the simplest of semantic things. For example, why not assume that when I search for two names strung together that they should be treated as if they were in quotes? That way I would find only that persons name and not First name only followed by various other last names or Last name only followed by various first names.

jimpeake 03/28/09 07:40:37 PM EDT

Seth: Maybe Brooke wanted to rank for the kw phrase in Google which she has for "semantic intelligence." Althought you are technically correct, all the client cares about is what can you do for me, what problems are you solving and what is it going to take to get it done? I'm working with a Boston seamntic search engine and consulting firm http://myroar.com and I can tell you clients don't care what we call it.

SethGrimes 03/27/09 07:31:00 AM EDT

Brooke, if you call this stuff "semantic intelligence," noone is going to want to use it, eh? Really, as you observe, it's business intelligence, brought back to its roots in unstructured (document) sources, best delivered via suitably extended search and BI interfaces and line-of-business applications.

Of course, Google already has a basic level of "semantic intelligence." It lemmatizes (e.g., stems) search terms and it does basic Question Answering. Type "4+5" or "map philadelphia" or "ORCL" or "weather 20912" into the Google search box to see.

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