Logic and inductive logic programming 邏輯與歸納邏輯程序設(shè)計
Inductive logic programming 歸納邏輯程序設(shè)計
This dissertation concentrates on the initial research work in genetic inductive logic programming technique 本論文主要開展了遺傳歸納邏輯程序設(shè)計技術(shù)的初步研究。
First - order rule mining technique based on first - order logic is often called as inductive logic programming ( ilp ) 基于一階邏輯的一階規(guī)則挖掘技術(shù)常被稱作歸納邏輯程序設(shè)計( ilp ) 。
We came up with algorithm descriptions and reinforced our conclusion by means of real testing examples . some data mining techniques , which can be applied to semantic web mining , were also discussed in this thesis . we explored the suitability of inductive logic programming ( ilp ) method in semantic web mining in more detail , and showed how to make use of this method in the semantic context 對于語義web挖掘中適合的數(shù)據(jù)挖掘技術(shù)進行了探討,提出了可采用歸納邏輯程序設(shè)計作為適合語義化web的數(shù)據(jù)挖掘技術(shù),給出了如何應(yīng)用這種技術(shù)的算法描述,并通過具體實例驗證了這種方法對于語義化web環(huán)境下進行數(shù)據(jù)挖掘是可行性。
Inductive logic programming (ILP) is a subfield of machine learning which uses logic programming as a uniform representation for examples, background knowledge and hypotheses. Given an encoding of the known background knowledge and a set of examples represented as a logical database of facts, an ILP system will derive a hypothesised logic program which entails all the positive and none of the negative examples.