Category Archives: Smart Search
23 Feb Inference in Knowledge Apps
In Section 5 we discussed different kinds of knowledge, including existential or hierarchical knowledge and causal knowledge. In Section 7 we discussed modeling approaches and search techniques that could be applied to any kind of knowledge. We saw that causal knowledge can be modeled as chains of causes and effects, and that existential knowledge can be […]
26 Jan Give Me Smart Requirements
I know how to solve this problem! I’ll just blast it to smithereens – Fire – Aim – Ready. Artificial Intelligence (AI) has been explored and developed in universities and startup companies throughout the developed world for decades, but is still struggling to reach the mainstream. There are many companies that effectively use intelligent processes and […]
07 Jan What’s in a Decision
A decision by any other name would feel as risky Take any class of software and you can find some structures or processes that you can associate back to some human-like structure or processes. To keep this more simple and relevant, I am focused on looking at systems that are fundamentally designed to replicate more […]
29 Dec Unhuman Expertise
Artificial Intelligence has suffered from a persistent scale problem: up to now, many techniques have been shown to work well and reliably in narrowly defined domains, but outside the domains of their expertise, they fall apart very quickly. No techniques of which I am aware, have exhibited common sense in the way we expect humans […]
17 Dec Visualizing Knowledge
Visualizing Knowledge – Automatic Generation Words are so symbolic that even symbolic thinkers, like me, understand more when there’s a picture to go along with the words. is partly explains my crazy use of images in this blog. The various forms of graphical representations are superb inventions that enable us to view and understand mathematical data […]
10 Dec Measuring Knowledge
Sometimes you need to know about your knowledge. When you’re in the middle of trying to build a system that knows stuff, you may ask, how much does the system know after this training or learning cycle as a percent of the total knowable amount? When we test students in their learning cycles, we use a […]
26 Nov Planning and Scheming
Select a Knowledge Representation (KR) Scheme In prior posts I have been describing the steps of building knowledge systems. A major part of Step 3: Task 1 is defining how to store knowledge – selecting a scheme. Giarratano and Riley (1989) suggest making the selection of a scheme, such as rules, frames or logic, dependent upon […]
28 Jul Patterns in the Mind
As we look for suitable solution designs for representing the knowledge and processes we humans use to communicate, we realize that we have no idea what knowledge in the brain looks like. Further, we only have relatively vague ideas about the processes that occur in the brain as we produce and comprehend words, phrases and sentences. […]
24 Jul Pattern Classification in Space
Pattern Classification Visual patterns can be recognized and classified based on prior knowledge: I see that this hairy animal has four legs and is about the same size as my dog, so I’ll assume it is (or classify it as) a dog. This may not be a correct classification, but it’s more correct than classifying it […]
07 Jul SPARQL Fireworks
How do you get at knowledge in conceptually structured information stores such as graphs? There are multiple ways to get data and information in broad use today. The most common is Structured Query Language (SQL) which is used as the almost universal access formalism for getting, storing and manipulating data in relational databases. An emerging standard […]