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

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發(fā)表于 2025-3-28 16:12:42 | 只看該作者
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發(fā)表于 2025-3-29 03:26:50 | 只看該作者
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發(fā)表于 2025-3-29 07:26:43 | 只看該作者
Term comparisons in first-order similarity measures,er can be gained by allowing lists and other terms in the input representation and designing similarity measures that work directly on these structures. We present an improved similarity measure for the first-order instance based learner . that employs the concept of . to efficiently compute distanc
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發(fā)表于 2025-3-29 22:46:08 | 只看該作者
Using prior probabilities and density estimation for relational classification,mation. Estimated densities and defined prior are combined in Bayes theorem to perform relational classification. An initial application of the technique is made to part-of-speech (POS) tagging. A novel use of Gibbs sampling for POS tagging is given.
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發(fā)表于 2025-3-30 01:38:54 | 只看該作者
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發(fā)表于 2025-3-30 06:55:50 | 只看該作者
A hybrid approach to word segmentation, First, a bias for word segmentation is introduced and a simple genetic algorithm is used for the search of segmentation that corresponds to the best bias value. In the second phase, the segmentation obtained from the genetic algorithm is used as an input for two inductive logic programming algorith
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