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ARTMED
2006
108views more  ARTMED 2006»
13 years 7 months ago
Constructing explanatory process models from biological data and knowledge
We address the task of inducing explanatory models from observations and knowledge about candidate biological processes, using the illustrative problem of modeling photosynthesis ...
Pat Langley, Oren Shiran, Jeff Shrager, Ljupco Tod...
IFIP12
2008
13 years 9 months ago
P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...
Frederic T. Stahl, Max A. Bramer, Mo Adda
AAAI
1996
13 years 9 months ago
Learning to Parse Database Queries Using Inductive Logic Programming
This paper presents recent work using the Chill parser acquisition system to automate the construction of a natural-language interface for database queries. Chill treats parser ac...
John M. Zelle, Raymond J. Mooney
LRE
2006
173views more  LRE 2006»
13 years 7 months ago
Automatic induction of language model data for a spoken dialogue system
When building a new spoken dialogue application, large amounts of domain specific data are required. This paper addresses the issue of generating in-domain training data when litt...
Chao Wang, Grace Chung, Stephanie Seneff
TYPES
2000
Springer
13 years 11 months ago
An Inductive Version of Nash-Williams' Minimal-Bad-Sequence Argument for Higman's Lemma
Higman's lemma has a very elegant, non-constructive proof due to Nash-Williams [NW63] using the so-called minimal-bad-sequence argument. The objective of the present paper is ...
Monika Seisenberger