by Werner Winiwarter, Yahiko Kambayashi
Proc. of the Workshop on Computational Natural Language Learning
http://acl.ldc.upenn.edu/W/W97/W97-1015.pdf
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Abstract:
In this paper we present first results from a comparative study. Its aim is to test the feasibility of different inductive learn-ing techniques to perform the automatic acquisition of linguistic knowledge within a natural language database interface. In our interface architecture the machine learn-ing module replaces an elaborate semantic analysis component. The learning module learns the correct mapping of a user's input to the corresponding database command based on a collection of past input data. We use an existing interface to a produc-tion planning and control system as evalu-ation and compare the results achieved by different instance-based and model-based learning algorithms. 1
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