Arun, (01)
We have been developing a tool that takes in natural language, produces an
Ontology, updates a dictionary, generates a "reader" application (to
semantically search a natural language corpus) and produces a report with
bibliography and hyperlinks. After 8 years, we are about to enter controlled
beta testing now. Let me know if you are interested in a demo. (02)
Chuck Rehberg, CTO
Semantic Insights
A Division of
Trigent Software (03)
-----Original Message-----
From: ontology-summit-bounces@xxxxxxxxxxxxxxxx
[mailto:ontology-summit-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Arun
Sent: Wednesday, March 02, 2011 3:32 PM
To: Ontology Summit 2011 discussion
Subject: Re: [ontology-summit] An example of the worth of ontology
development (04)
Does anyone have any tools that go from raw data to produce Ontologies
as output or even proto-ontologies as outputs that humans can then edit
and refine? (05)
On 3/2/11 12:50 PM, Jack Ring wrote:
> Quite so.
> That's why helping them understand their enterprise as a system, hopefully
an intelligent system, gives them the perspective to grok the strange
distinctions that ontologists need to make.
> This starts with a little semantic modeling; then activity modeling of the
problematic situation (customers, markets, competitors, etc., and Their
customers, markets, competitors, etc.,); then formulating an intervention
strategy for serving unmet, even unrecognized, market needs better than can
competitors and rivals; then design/architecture of To Be enterprise; then
> teasing out the infrastructure and modularization. All this must precede
the development on ontology (because ontology is a major facet of
infrastructure).
>
> Ways of accomplishing intelligent enterprise systems architecting and
engineering are being evovled.
>
> Unfortunately the NOISE created by Business Process Management, Knowledge
Management, Business Rules management, Enterprise Architecture Frameworks
(for paint-by-numbers, i.e., ignorant, enterprises), etc., is precluding
rapid development of this capability.
>
> Meanwhile, there are already places that have recognized the need for
intelligent infrastructure. These are the current market targets for
ontology insertion. In general, it is any enterprise or market wherein He
Who Learns Fastest Wins. Specific examples are Military Intelligence,
Business Intelligence, Conference Management (evolving to social network
interlocutor), Learning Management (as modern education of youth is finally
freed from government intervention), and Autonomous System engagement
management. Personalized, Molecular-level medicine may become the Killer
App.
>
> Make sense?
>
> On Mar 2, 2011, at 10:10 AM, John F. Sowa wrote:
>
>> Jack and Mike,
>>
>> I agree with that point, but I'd like to add some qualifications:
>>
>> JR
>>> The primary purpose of a semantic model is to facilitate knowledge
>>> exchange and choice making in a gaggle of humans in hopes of
>>> morphing the gaggle into a system. A key usage is to inform the
>>> development of an executable ontology, e.g., application software,
>>> for automation of information flow and decision. Another key purpose
>>> is to provide a basis for objective assessment of enterprise
>>> situation (aka evidence-based management).
>> MU
>>> Yes, this is the kind of thing I'm after.
>> The primary qualification is that the "gaggle of humans" can only
>> agree on what they understand. The people who work in a field
>> can all agree that a list of familiar words, as documented in
>> their familiar texts, cover their familiar subject matter.
>>
>> But when ontologists start to axiomatize those terms in some
>> arcane notation based on some arcane distinctions about
>> endurants, perdurants, continuants, etc., all bets are off.
>>
>> John
>>
>>
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