[topicmapmail] A Key Next Generation Application for TMs and like technologies
MARK DRAGAN
mithrndir@msn.com
Tue, 05 Nov 2002 21:09:39 +0000
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Hello,
I'm attaching a web page that introduces concepts that I've been nursing for
7-8 years. In the spirit of openness, I'd like to begin sharing them.
Mark Dragan
mithrndir@msn.com
_________________________________________________________________
Surf the Web without missing calls! Get MSN Broadband.
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<h1><span style='font-size:18.0pt;mso-bidi-font-size:16.0pt'>A Missing Key For
Next Generation Applications <o:p></o:p></span></h1>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>This paper introduces a next generation information
processing application capable of shifting XML, Topic Map, Semantic Web, and
Knowledge Management technologies into overdrive, turning e-commerce upside-down,
and helping to combat cyber-terrorism. This application seems neutral to the
technology upon which it runs, so it may not matter whether it runs uses web
services or not. Web services may enhance its usefulness, but that remains to
be seen. </p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>There have been various attempts to find common ground among
XML, Topic Map, RDF, Semantic Web, Knowledge Management, and Knowledge
Organization technologies. Though some research has focused on the use of
dictionaries and thesauri, a key application of that data has been overlooked.</p>
<p class=MsoNormal>In the spirit of openness, I’d like to share an application
that, in its use of such data, holds the potential for achieving a sought after
convergence of these technologies and the means by which they can begin to
realize their full potential. </p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>Over the past seven to eight years, I’ve been exploring the
usefulness of what seems, on the surface, a ridiculous notion, that is, making
a concordance of the dictionary. Though thesauri and other references would
also likely play a part, this application is easier to envision by limiting the
initial discussion to the dictionary. Likewise, for convenience, I’ll use the
term Geodesic Database or Geodesic Dictionary (GD, for short), to represent a
neutral, non-aligned vision of the convergence of these technologies. Notice
the similarities in the images conjured by: </p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.25in;mso-list:l1 level1 lfo1;
tab-stops:list .5in'><![if !supportLists]><span style='font-family:Symbol'>·<span
style='font:7.0pt "Times New Roman"'>
</span></span><![endif]>A world-wide semantic network of interconnecting nodes
spanning the globe,</p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.25in;mso-list:l1 level1 lfo1;
tab-stops:list .5in'><![if !supportLists]><span style='font-family:Symbol'>·<span
style='font:7.0pt "Times New Roman"'>
</span></span><![endif]>A world-wide 3D lattice of interconnecting nodes
communicating to Geo-stationary satellites used in Topic Map circles, and </p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.25in;mso-list:l1 level1 lfo1;
tab-stops:list .5in'><![if !supportLists]><span style='font-family:Symbol'>·<span
style='font:7.0pt "Times New Roman"'>
</span></span><![endif]>A Geodesic dome like the one in Epcot center in Disney
World in Florida, USA.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>Still, feel free, if you’re familiar with Semantic Webs, to
think Semantic Web instead of Geodesic Database. If you’re familiar with Topic
Maps, think Topic Maps instead of GDs, and so forth. </p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>Because the dictionary is fully self-referential, that is,
all of its words are defined by other words; a 3D representation of their
interconnections would resemble a complex geodesic dome (as it would resemble
both of the other models). To be more explicit, a database would result from a
parser traversed each word in the dictionary and its definitions. </p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>As it encountered each word, it would create a node for the
word, and a two-way link to every word in its definition. Of course, various
levels of intelligence could be used here to define additional link structures
based on parts of speech, whether there are synonyms, word roots, etc., but for
now, let’s keep it simple. The words and links would become “weighted” in the AI
sense, and would naturally form nested relationships between lower-level
concepts and higher-level concepts. </p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>Now, suppose (watch out, here comes the assumptions) that:</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.25in;mso-list:l0 level1 lfo2;
tab-stops:list .5in'><![if !supportLists]>1.<span style='font:7.0pt "Times New Roman"'>
</span><![endif]>There was a level of agreement as to what words would be
included in some base Geodesic Dictionary (a.k.a. GD) (which would of course
define how each node was initially weighted), which could include translations.</p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.25in;mso-list:l0 level1 lfo2;
tab-stops:list .5in'><![if !supportLists]>2.<span style='font:7.0pt "Times New Roman"'>
</span><![endif]>Systems could process this information efficiently.<span
style="mso-spacerun: yes"> </span></p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.25in;mso-list:l0 level1 lfo2;
tab-stops:list .5in'><![if !supportLists]>3.<span style='font:7.0pt "Times New Roman"'>
</span><![endif]>This GD and its initial weightings define a starting point, a
“table Rasa”; that is, a GD whose content and weights have not been affected by
interactions with other GDs, documents, databases, search engines, and so
forth. This provides a standardized starting point from which additional
“experience-based” weightings can be added and compared with other GDs.</p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.25in;mso-list:l0 level1 lfo2;
tab-stops:list .5in'><![if !supportLists]>4.<span style='font:7.0pt "Times New Roman"'>
</span><![endif]>There is software capable of comparing the weights in one GD
to another and identifying the deltas though time.</p>
<p class=MsoNormal style='margin-left:.5in;text-indent:-.25in;mso-list:l0 level1 lfo2;
tab-stops:list .5in'><![if !supportLists]>5.<span style='font:7.0pt "Times New Roman"'>
</span><![endif]>There is software capable of crawling through various forms of
information, extracting the words there, and using them to add weight to the
words in the “table Rasa” GD. (remember that more complex approaches would
include adding new words, and dealing with other forms of data, such as video
and audio, but let’s keep it simple, for now).</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>Okay, nothing too complex here. These assumptions are easy
enough to swallow. Now, What? What do you do with a table Rasa Geodesic
Database of dictionary items?</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>Perhaps, like all businesses, your company’s accounting
department wants to access and interact with the company data from its point of
view, as do the executives, the marketing department, the IT department, and so
forth. You might, again create a table Rasa GD for each department that records
the types of information, <i>and functions</i>, that members in each department
access, then customizes their interfaces to bring that information and those
functions to them. With experience (or with a bit of pre-set weightings
garnered from the experiences of similar departments in similar businesses –
see the possibilities for remarketing weighted templates), the information, and
functions that a particular department is likely to want, can be pre-served for
them. This has many implications for Web Services.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>Perhaps you’d like to evolve a personal search agent that
automatically “learns” your shopping interests. You could activate software on
your computer that creates a new GD that begins adding weight to those words
that it encounters as you interact with web pages. This results in a
personalized GD that is weighted to your shopping interests. After developing
this profile, you send it out on the web to crawl around and weed through
various sites and search engines to determine if those sites have similarly
weighted content. After finding those sites, it brings them to your attention. </p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>Such agents could turn the e-commerce paradigm upside-down
and address many security concerns. Suppose that your shopping agent GD doesn’t
exist on your computer, but resides on a separate server. Further suppose that
it has your shopping and interests preferences, and your contact’s lists. Since
you’ve blocked all ads and email to your computer and have a very secure
channel to your agent, marketers will target your agent rather than you. This
empowers your agent to automatically filter through the marketing information.
It also allows it to proactively shop for goods and information for you. This
paradigm will serve the marketers, because the GD will automatically, and more
efficiently, hook them up with targeted customers. It creates a win-win
experience for businesses and consumers. It also may make security more
achievable.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>Take this concept into the Web Services arena. A scenario
emerges where GD weights could evolve to help load balancing among servers and
applications. Suppose a user’s agent begins to use the services, perhaps
locally on the same server (the agent software can itself be mobile). Suppose
further that the Web Services server determines, by the nature of the agents
weighting, what applications it is likely to use during its interactions. Such
foreknowledge would enable the Web Services to work more effectively.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>In the software development industry, one could use such
technology to determine what code components are useful to what industries. It
could also determine what functions are obsolete, and which ones to reuse. It
might even be able to “learn” what parts of a function are more valuable than
others.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>For software testing, GDs could define various test
scenarios and user profiles that would form useful test cases. </p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>Hardware and chip manufacturers could finally introduce
large-scale parallel processing systems.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>Business executives could create GDs capable of discovering
and “learning” about the major factors confronting their business, just by
letting such a system monitor its interactions with customers, including
documents, contracts, etc., thus building a picture of its major activities, in
either a short-or long-term capacity. It could report on the percentages of
time used for various activities in its daily business, either by its systems
or by its employees.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>User interfaces could be freed from the file-drawer
paradigm. More natural interfaces could be developed, that when a client calls,
the system serves up links to that client’s contracts, related correspondences,
personal information, accounts payable, accounts receivable, and so forth.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>National security could help to monitor massive amounts of
message traffic (perhaps even encoded) to determine variations from the normal
types and amounts of messages. </p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>It could make cheap parallel processing possible.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>In the financial industry, a GD could help determine
variations in the marketplace and help illuminate trends.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>On the commercial side a GD could help identify buying
patterns, both over time, and across market segments. </p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>Supply-chain management could benefit from a series of GDs
that were weighted to trigger when ordering more supplies was necessary. </p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>GDs could help process management if their weights were
“tuned” to the various stages in the process, and serve the appropriate set of
functions, documents, etc. as the product passed through each process stage.</p>
<p class=MsoNormal><span style="mso-spacerun: yes"> </span></p>
<p class=MsoNormal>In the research arenas, GD could make it easier for
researchers to find existing research by tuning the GDs weights to focus on the
target information.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>GDs could be used in satellite imaging and communication
applications such as detecting environmental changes, and spotting military
targets. Only needing to send changes to images or other data in the stream may
reduce communication bandwidth.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>A GD approach could be used in pattern and image recognition
systems by being able to detect variations in an automated, continuous scan
mode. This has obvious military applications.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>GDs may make it easier to combat terrorism and
cyber-terrorism by being able to detect anomalies to the normal types of
messages sent without needing to investigate the content of every message.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>As you can see, the applications for this approach are
endless. </p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>This model is both flexible and scaleable. It is flexible in
the sense that comparisons can be made on any part of the GD, and it can be
translated between cultures and across disciplines. It is also flexible in the
sense that its approach is not limited to words. GDs could be composed of
pictorial nodes and their definitions, or sound frequencies and their
definitions, and so forth. It is scaleable in the sense that the starting
point, table Rasa GD, is not set in stone. It can evolve to include any number
of terms, the difference measurable. It is also scaleable in the sense that the
quality of the linkages between nodes can be improved by adding additional
intelligence into the generation of the GD, making it increasingly rich in
complexity. This also enables you to directly measure the differences among
versions. </p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
<p class=MsoNormal>For related information including how to integrate
humanistic attributes into business and technical processes, components, and
information systems that span cultures and disciplines, see
www.humancontexttechnologies.com.</p>
<p class=MsoNormal><![if !supportEmptyParas]> <![endif]><o:p></o:p></p>
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