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the semantic web a gide to the future of XML, Web Services and Knowledge Management - Daconta M,C.

Daconta M,C. the semantic web a gide to the future of XML, Web Services and Knowledge Management - Wiley publishing , 2003. - 304 p.
ISBN 0-471-43257-1
Download (direct link): thesemanticwebguideto2003.pdf
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Addition (|nteger Typ^K X | X e Universe of
C°nstan^ |nteger Discourse
Type Constant) /„no ,
Negation Boolean ^ [[Addit«>n (4 e {1, 2.........n}, Î
Type (Boolean Type
Boolean Type
* Where [[X]] signifies the truth value of the expression X
Figure 8.5 From simple to complex semantics.
e {1, 2 n}U]
- (X | Xe {t, f} v Y e {t, f})]]
Complex Semantics More Complex Semantics
{“zDLKFL” e {“a”, “b”, “c”,..., infinite
{12323} e {1, 2, ..., n} X | X e {1, 2, ..., n} X | X e Universe of Discourse [[Addition (4 e {1, 2, n}, 3 | Y e {1, 2, ..., n})]]
[[ - (X | X e {t, f} v Y e
{t, f})]]
X | ((X e Thing a Thing □ Universe of Discourse) v (X e Person a Person □ Universe of Discourse), v ■■■ )
[[Addition]] ({4}, {3}) = {7}
* Where [[X]] signifies the semantic or truth value of the expression X
Figure 8.6 More elaborated semantics.
Understanding Ontologies
Obviously, the machine semantics is very primitive, simple, and inexpressive with respect to the complex, rich semantics of humans, but it's a start and very useful for our information systems. The machine is not "aware" and cannot reflect, obviously. It's a formal process of semantic interpretation that we have described—everything is still bits. But by designing a logical knowledge representation system (a language that we then implement) and ontologies (expressions in the KR language that are what humans want to model about our world, its entities, and the relationships among those entities), and getting the machine to infer (could be deduce, induce, abduce, and many other kinds of reasoning) conclusions that are extremely close to what humans would in comparable circumstances (assertions, facts, and so on), we will have imbued our systems with much more human-level semantic responses than they have at present. We will have a functioning Semantic Web.
Pragmatics sits above semantics and has to do with the intent of the semantics and actual semantic usage. There is very little pragmatics expressed or even expressible in programming or databases languages. The little that exists in some programming languages like C++ is usually expressed in terms of pragmas, or special directives to the compiler as to how to interpret the program code. Pragmatics will increasingly become important in the Semantic Web, once the more expressive ontology languages such as RDF/S and OWL are fully specified and intelligent agents begin to use the ontologies that are defined in those languages. Intelligent agents will have to deal with the pragmatics (think of pragmatics as the extension of the semantics) of ontologies. For example, some agent frameworks, such as that of the Foundation for Intelligent Physical Agents (FIPA) standards consortium,6 use an Agent Communication Language that is based on speech act theory,7 which is a pragmatics theory about human discourse that states that human beings express their utterances in certain ways that qualify as acts, and that they have a specific intent for the meaning of those utterances. Intelligent agents are sometimes formalized in a framework called BDI, for Belief, Desire, and Intent.8
In these high-end agents, state transition tables are often used to express the semantics and pragmatics of the communication acts of the agents. A communication act, for example, would be a request by one agent to another agent concerning information (typically expressed in an ontology content language
6See the FIPA home page (, especially the specification on Communicative Acts under the Agent Communication Language ( repository/cas.php3).
7See Smith (1990) for a philosophical history of speech act theory in natural language.
8See Rao and Georgeff (1995).
Chapter 8
such as Knowledge Interchange Format [KIF])9—that is, either a query (an ask act, a request for information) or an assertion (a tell act, the answer to a request for information). When developers and technologists working in the Semantic Web turn their focus to the so-called web of proof and trust, pragmatic issues will become much more important, and one could then categorize that level as the Pragmatic Web. Although some researchers are currently working on the Pragmatic Web,10 in general, most of that level will have to be worked out in the future.
Table 8.2 displays the syntactic, semantic, and pragmatic layers for human language; Table 8.3 does the same for intelligent agent interaction. In both cases, the principles involved are the same. Note that the levels are numbered from the lower syntactic level upward to the semantic and then pragmatic levels, so both tables should be read from bottom to top. In all the examples (1 to 3), you should first focus on the question or statement made at the top row. In Example 1 in Table 8.2, for example, you ask the question "Who is the best quarterback of all time?" The answer given to you by the responder is the string represented at the syntactic level (Level 1), that is, the string "Joe Montana". The literal meaning of that answer is represented at the semantic level (Level 2), in other words, The former San Francisco quarterback named Joe Montana. The pragmatic level (Level 3) shows that the response is a straightforward answer to your question "Who is the best quarterback of all time?" This seems simple and reasonable. However, looking at Example 2, we see that there are some complications.
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