
state machine and perform varied behaviors
depending on what was received. Content transfer
has recently become a widely discussed topic, and
the extensible Markup Language (XML) was
introduced largely to enable such goals. With a
simple, standardized syntax in place, developers
using XML are able to spend more time considering
the semantics of their communications instead of
their format.
Knowledge transfer represents the pinnacle of
our simple classification of communications. Just as
content transfer required data transfer, so knowledge
transfer requires content transfer. This time,
however, we expect the recipient not only to accept
and process the content, but also to actually know
when it has learned something new and proceed to
reason about the consequences of the additional
knowledge. The consequences may include such
high-level notions as the mental state of the sender.
The important distinction here is that at least one of
the communicating parties is capable of reasoning.
It is important to note that for stretchability it is
sufficient to enable content-transfer. The additional
requirements implied by knowledge transfer,
especially that of mental state, are not necessary to
engage in useful communication. In fact, we submit,
that if we engender our agents with mental states,
then we endanger our prospects for honest,
purposeful communications. We further suggest that
a considerable amount of human language is
dedicated to the purposes of evasion and dishonesty,
with secondary importance placed on comforting our
kinsmen. The additional purpose of transferring
relevant information ranks far lower when
measuring the motivations for natural language
design. However, in the context of C2B, it is the
low-ranked goal of content-transfer that acquires
ultimate importance.
What we need then is a new content biased
language (CBL) that allows software agents to
successfully communicate details regarding their
requirements within a transaction. This new
language must achieve the following goals:
· Obtain agreement on the semantic meaning
of lexemes.
· Establish the unique identity of a referent.
· Represent any concept at any level of
granularity.
· Represent any relationships that may occur
between concepts, including relational, non-
relational, Cambridge, and comparative relations.
· Distinguish the use of the same concept in
different contexts without always discussing all
aspects of the concept and without losing the
importance of the specific context.
· Factor time and object evolution into the
model.
· Construct the scaffolding such that any model
of any physical-behavioral unit can be modified and
reused, including direct reference from any other
model of any other physical-behavioral unit.
· Enable a means of expressing the rationale or
intentions behind an individual’s decision to make
data accessible.
· Ensure that the description of intentions with
content is orthogonal to the content itself.
· Ensure that partial content is understood as a
subset of total content, and the functionality of an
agent is not inexorably halted when presented with
partial content.
5 CONTENT BIASED LANGUAGE
(CBL)
In general, a language is composed of two distinct
components, the vocabulary and the grammar. The
vocabulary defines the lexical elements of the
language, and the grammar defines the syntactical
rules for combining the elements. The semantics
implied by certain syntactically valid constructions
form yet another important dimension of language.
In the case of our content biased language, the
vocabulary will be referred to as an External Open
Ontological Type System (EOOTS). This follows
directly from the fact that the language will serve as
a type system but also has properties of an ontology.
When an agent receives a request-for-content, it
must understand what information the sender is
requesting. Likewise, when that agent sends back a
reply-with-content, the original sender must
understand the response. There are a number of
approaches that can be applied to achieve this goal.
The immediate solution is to create a standardized
content representation vocabulary that all
communicating agents must use. Note that a markup
language such as XML is not, in and of itself,
sufficient to achieve this goal. Simply because an
agent can utilize a standard XML parser to extract
the data from the XML document, does not imply
that the data points have any particular significance.
Thus, the problem we are trying to solve is not one
of simply parsing out the individual data values
within a message, but rather one of comprehending
the significance of those values - that significance is
conveyed by the semantic layer logically situated
atop the EOOTS.
The English language, or more accurately an
English Language Dictionary, may be considered a
repository of words. Each word represents one or
more concepts, as described by the definition of the
word, and made real by acceptance and use in
everyday dialog. In much the same way, the content
A CONTENT ORIENTED ARCHITECTURE FOR CONSUMER-TO-BUSINESS E-COMMERCE
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