I am working on a similar technology for at least 5 years now, a lot less
money behind it (unfortunately) and not related to Google. (01)
It doesn't surprise me that it is not available yet, because the tree/graph
(really a snapshot in a network) is extracted human knowledge. It needs to
be negotiated and long term collected. I don't think you can just run some
statistical probability on what concepts belong together, what are similar
to each other, what are [any number of semantic relations here] to each
other. (02)
The graphs are snapshot views into the semantic network and they allow
concept identification even by describing the concept instead of using
string comparisons, probabilities and ranking (assuming enough relationships
are available). (03)
I additionally have a mechanism to link language presentations to the
concept and can generate a concept description in foreign languages. (04)
This architecture lends itself for question and answering as well (in any
language). Since the system identifies partial semantic networks it can
formulate questions about the missing link or rephrase a question/statement
if someone doesn't understand (e.g. in another language). (05)
The question to be asked here is: What is the purpose of this? For
advertising I think string matching will (and has been) doing fine. For
knowledge sharing, knowledge modeling (and agile code generation), true
machine translation (where the machine "understands" the context of the
translation), etc. you need this stuff. (06)
I can see a new form of operating system here, a knowledge device that
allows to sync up and share knowledge of/with others, maybe even as a
universal translation device. (07)
Tom (08)
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