Titlebook: Inductive Logic Programming; 8th International Co David Page Conference proceedings 1998 Springer-Verlag Berlin Heidelberg 1998 Algorithmic

GIBE

Learning multilingual morphology with ,,ile FOIDL is, due to efficiency reasons, severely limited in the size of the training set, CLOG does not suffer from such limitations. With the increase of the training set size possible with CLOG, it significantly outperforms FOIDL and learns highly accurate morphological rules.

開頭

Repeat learning using predicate invention, learning experiments within a chess domain. The results indicate that significant performance increases can be achieved. The paper develops a Bayesian framework and demonstrates initial theoretical results for repeat learning.

騎師

Strongly typed inductive concept learning,n Escher, a typed, higher-order, functional logic programming language being developed at the University of Bristol. We argue that the use of a type system provides better ways to discard meaningless hypotheses on syntactic grounds and encompasses many . approaches to declarative bias.

Banister

Application of inductive logic programming to discover rules governing the three-dimensional topoloearly stage of development, the rules produced can only be applied to proteins for which the secondary structure is known. However, since the rules are insightful, they should prove to be helpful in assisting the development of taxonomic schemes. The application of ILP to fold recognition represents a novel and promising approach to this problem.

狗舍

A stochastic simple similarity,similarity function with controllable complexity. Preliminary experiments on the well-studied mutagenesis problem (regression-friendly and regression-unfriendly datasets) demonstrate the potential and the limitations of this similarity.

justify

Induction of Constraint Grammar-rules using Progol,is a realistic way of learning rules of good quality with a minimum of manual effort. When tested on unseen data, 97% of the words retain the correct reading after tagging leaving an ambiguity of 1.15 readings per word.

Axon895

notice

Stochastic propositionalization of non-determinate background knowledge,thm to automatically derive features from non-determinate background knowledge. The algorithm conducts a top-down search for first-order clauses, where each clause represents a binary feature. These features are used instead of the non-determinate relations in a subsequent induction step. In contras

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Armory