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April 3, 2008

Cyc is more than encyclopedic

I had the pleasure of visiting with some fine folks at Cycorp in Austin, Texas recently.  Cycorp is interesting for many reasons, but chiefly because they have expended more effort developing a deeper model of common world knowledge than any other group on the planet.  They are different from current semantic web startups.  Unlike Metaweb‘s Freebase, for example, Cycorp is defining the common sense logic of the world, not just populating databases (which is an unjust simplification of what Freebase is doing, but is proportionally fair when comparing their ontological schemata to Cyc’s knowledge).  Not only does Cyc have the largest and most practical ontology on earth, they have almost incomprehensible numbers of formulas[1]  describing the world.   (more…)

February 19, 2008

Understanding events and processes takes time

We have been teaching a computer to answer questions like, “How much did IBM’s earnings change last quarter?”  It takes a fair bit of knowledge, including how to understand English, to answer this question.  But teaching it what a “quarter” is brought back memories of debates with some former CMU colleagues about what units are and how to model time.  Since quite a few people ask me for help with knowledge engineering and ontological matters, I thought some might be interested in parts of those debates.As you will see, a strong upper ontology of common knowledge is required to understand common business knowledge.  Leveraging such an ontology is the only way to deliver business rules for under $50.

Sentences like “do something if more than a number of possibly related things have happened within a timeframe of something else happening” or “do something if nothing happens within a timeframe following something happening” are extremely common in business process management (BPM), complex event processing (CEP), and workflow.  With a sense of time, a business rules management system (BRMS) can support BPM, CEP, and workflow applications almost trivially.  Without a sense of time, most BRMS force users to perform computations.  

For example, without a sense of time and an infrastructure that supports it, the sentence “call a customer if no response is received within 30 days of notifying the customer of a delinquency” has to be transformed into something like “if a notice is mailed on a date and the notice is a delinquency and the date of notification has a day number then compute the date for checking by adding 30 to the day number and check for a response to the delinquency notice on the date for checking”.  The checking on a date for a response to a notice must also be implemented as a database (or persistent queue) of events to be polled or triggered by application code.  Then a second rule is required to implement the check, as in “if checking whether a response has been received to a notice and the notice was given on a date of notice and the notice was given to a customer and there exists no record of communication with the customer since the date of notice then call the customer”.  (Note that this is actually how most BRMS products would implement this.  The natural language approach I prefer handles the original sentence.)

The discussion here reflects the general structure and content that a usable ontology for business process management requires.  Most users of business rules management tools will find the need to understand and engineer this discussion in their tool of choice.  As my Haley Systems customers know, much of this is reflected in Authority’s built-in ontology and English vocabulary, but quite a few of the points discussed here reflect improvements, especially concerning the confusion between units and amounts.

As you will see the discussion takes careful thinking.  Some readers may find it onerous.  If at any time you have had enough (or if you simply cannot take anymore!), please skip to the end and decide whether to fill in the conclusions by revisiting the body.


January 31, 2008

The $50 Business Rule

Work on acquiring knowledge about science has estimated the cost of encoding knowledge in question answering or problem solving systems at $10,000 per page of relevant textbooks.  Regrettably, such estimates are also consistent with the commercial experience of many business rules adopters.  The cost of capturing and automating hundreds or thousands of business rules is typically several hundred dollars per rule.  The labor costs alone for a implementing several hundred rules too often exceed $100,000.

The fact that most rule adopters face costs exceeding $200 per rule is even more discouraging when this cost does not include the cost of eliciting or harvesting functional requirements or policies but is just the cost of translating such content into the more technical expressions understood by business rules management systems (BRMS) or business rule engines (BRE).

I recommend against adopting any business rule approach that cannot limit the cost of automating elicited or harvested content to less than $100 per rule given a few hundred rules.  In fact, Automata provides fixed price services consistent with the following graph using an approach similar to the one I developed at Haley Systems.

Cost per Harvested or Elicited Rule


December 11, 2007

Managing Semantics, Vocabulary and Business Rules as Knowledge

A client recently asked me for guidance in establishing a center of excellence concerning business rules within their organization. Their objectives included:

  1. Accumulate requisite skills for productive success.
  2. Establish methodologies for productive, reliable and repeatable success.
  3. Accumulate and reuse content (e.g., definitions, requirements, regulations, and policies) across implementations, departments or divisions.
  4. Establish multiple tutorial and reusable reference implementations, including application development, tooling, and integration aspects.
  5. Establish centralized or transferable infrastructure, including architectural aspects, tools and repositories that reflect and support established methodologies, reusable content, and reference implementations.
  6. Establish criteria, best practices and rationale for various administrative matters, especially change management concerning the life cycles of content (e.g., regulations or policies) and applications (e.g., releases and patches).

I was quickly surprised to find myself struggling to write down recommendations for the skill set required to seed the core staff.  My recommendations were less technical than the client may have expected.   After further consideration, it became clear than any discrepancy in expectations arose from differences in our unvoiced strategic assumptions.  Objectives, such as those listed above, are no substitute for a clearly articulated mission and strategy.  


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