|From:||FERENC KOVACS <f.kovacs@xxxxxxxxxxxxxx>|
|Date:||Sat, 21 Aug 2010 08:06:08 +0000 (GMT)|
I have a homework to do, namely to sum up what and how AI technology combined with ontologies are used for outsiders (like myself as well). May I ask you to take a glance at the passages below and tell me if anythig is wrong with such an interpretation. Thank you.
Semantic analysis in AI starts from syntactically parsing a text or other sequences of signals to see if the statements (valid chunks) are well formed. Then the statements are analysed semantically against a set of axioms laid down beforehand to see if the semantic content of the statements ise adequate, i.e. if it is true. Then on the basis of true statements,conclusions are drawn, and this process is called reasoning. The statements in the input text refer to the real world and their validity is tested against the axioms consising of other statements about the real world.
The input text is written either in a controlled language or a in formal language which are in turn described in a normal form in the sense that nothing is left undefined. For instance in using BNF every sign/symbol in the language is defined recursively, in terms of other symbols and there is a basic set of terminal symbols that are used to generate statements. The process of semantically analysing texts is in fact a syntactic analysis, which requires that all symbols/names should be unique, otherwise it is not possible to make a decision, or serve the purpose of the procedure.
Thus the objective of AI and automated reasoning is to support real life decision systems. AI applications are focused on particular domains and are normally „complete” or closed with respect to those domains. The data that they rely on are in database formats and syllogisms are used to draw conclusions from premises that are embodied in the axioms on the basis of which input data are tested.
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