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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…)

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 31, 2007

Missing Goals and Requirements in Business Rules

Filed under: Business Rules, Formal Logic, Requirements, Rules Engines, Standards — Tags: , , , , , , , — paul@haleyAI.com @ 3:13 pm

Both of the following statements are true, but the first is more informative:

  1. Business Rules Management Systems (BRMS) typically produce forward chaining production rules that are interpreted by[1] a business rules engine (BRE) based on the Rete Algorithm.
  2. BRMS typically generate rules that are interpreted by a BRE.

First, dropping the word “production” before “rules” loses information. BRMS do not typically generate rules that are not production rules. Consider, for example, the BRMS vendors involved in the OMG effort produced the Production Rule Representation (PRR) standard. The obvious question is:

  • What is different about production rules?

Second, dropping the words “based on the Rete Algorithm” loses information. The dominant rules vendors and open-source engines are all based on the Rete Algorithm.

  • Why does the Rete Algorithm matter?

Third, dropping the word “chaining” before “rules” loses information. Chaining refers to the sequential application of rules, as in a chain where each link is the application of one rule and links are tied together by their interaction. But:

  • Why does chaining matter?

Fourth, dropping the word “forward” before “chaining” loses information. Forward chaining reacts to information without requiring goals. This begs the question:

  • Don’t goals matter?


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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