A Statistical Model to Verify Verbal Material
Abstract: In natural language processing up to now mainly rule-based
systems have been used. The rule-based approach has been successful
for limited domains, where the manual construction of the rules is feasible.
In recent studies, however, a need for the automatic generation of the rules
has been seen. On the other hand, when children learn their mother tongue no
explicit rules seem to be needed. Therefore, in our study we try to examine
how far we can get in natural language processing without any rules. Instead
we use a statistical approach. It is based on our previous work in the field
of associationism, but also takes up results obtained when using hierarchically
structured networks to significantly reduce the redundancy of texts.
Paper im Postscript-Format
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