Developer Demo V5

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The power of the associative memory base lies in the ability to create associations between multiple entities. Continuing with the example of the auto parts vendor, acme, we can see that this vendor supplies three types of parts: lamps, shields and mirrors. [click] it’s also possible to see that there is a relationship between acme and corrosion on parts

But with the Associative memory base we can create more complex relationships than between individual entities. [click]For example, if we look at the relationship between corroded acme lamps, we can see a connection. [click]The same is true for corroded acme shields. But there is no corrosion problem with acme mirrors. [click] These complex associations (also known as triples) are possible in the associative memory base

But there is an additional attribute of the Associative Memory Base that is just as important. If you are familiar with RDF then you know that the first, simple association I showed at the start can be represented by RDF. The entity – link – entity relationship is easy to define with RDF.

But in an Associative Memory Base we go one step further by defining exactly how strong the association is between entities. So in this example we can see a strong relationship between Lamps, weaker with shields and even weaker with mirrors (based on the width of the link)

This strength is nothing more than the count of occurrences between entities. The Associative Memory Base stores the frequency of associations between the Vendor Acme and the various parts.

We can use this information to give us the “strength” of the associations.

If we put frequency counts together with complex associations you can create an associative memory base. Consider the relationship between corrosion and our vendor, Acme. [click] If we look at that relationship, we see a weak association to shields and a stronger one to lamps.

This is the corrosion matrix that describes all the associations between entities starting with the description of corrosion. [click] let’s focus on that last line, which is the associations to corroded parts from acme [click] We can see that there are no acme mirrors or steel parts with corrosion [click] But there are counts for both acme lamps and shields.

That is where we get the strength of the associations in this graph

But other associations are apparent in the corrosion matrix. [click] if we look at aluminum [click] we can see corroded aluminum lamps and shields

This graph starts to get very complex very quickly as we navigate through the matrix, add in aluminum and the frequency counts. [click][click][click]

But part of the power of the associative memorybase is that we can see relationships between any entities, so we can see that the problem with corroded acme parts is really about the material, not the specific part involved.

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Developer Demo V5 - Presentation Transcript

Simple Associations vendor. acme part. shield part. lamp part. mirror description. rust
Complex Associations description. rust part. shield part. lamp part. mirror vendor. acme Complex Associations
RDF vendor. acme part. shield part. lamp part. mirror
Associative MemoryBase vendor. acme part. shield part. lamp part. mirror
Frequency Counts
Frequency Counts vendor. acme part. shield part. lamp part. mirror 1 4 9
Associative Memories part. shield part. lamp description. rust vendor. acme
Associative Memories “ Rust Matrix”
Associative Memories part. shield part. lamp 6 description. rust vendor. acme 3
Associative Memories “ Corrosion Matrix”
Associative Memories material. aluminium material. aluminium part. shield part. lamp description. rust vendor. acme 6 3
Associative Memories “ Corrosion Matrix”
Associative Memories description. rust vendor. acme material. aluminium 9