| 1. | A rule learning algorithm based on neural network ensemble
一种基于神经网络集成的规则学习算法 |
| 2. | And generating simple and strong rules which can used by information extraction module through rule learning arithmetic after training
训练结束后,根据规则学习算法学习生成简单、健壮的规则库,以供信息抽取模块使用。 |
| 3. | To solve the problem of rule learning time cost for traditional transformation based part of speech tagging method of latin mongolian , a dynamic partition algorithm was presented
针对传统基于转换的词性标注方法中规则学习速度过慢的问题提出了一种对训练语料库进行动态划分的算法。 |
| 4. | This thesis concentrates its research mainly on the method of rule learning base on bp neural network which definition of rules are combined the web pages ’ features of path , left / right boundary and semantic
本文的工作重点是基于bp神经网络的规则学习方法,规则的表示结合网页的路径特征、左右边界特征和语义特征来定义。 |
| 5. | The degree of propriety of a compound should be measurable . in this paper , we focus our attention on the rule learning of the second type of unknown words only . their morphological representation and the measurement for the propriety are studied
本论文将重心放在这类型的复合词上，我们提出以语法语意及统计机率关系表达开放型未知词组合成分的构词律模型，这个模型用来表达及测度复合词的结构合理程度。 |
| 6. | It including several knowledge repositories as well as three modules of web pages preprocessor , rule learning and information extraction , describing the web pages by four sides : semantic content display , logic structure , rule generation and extraction results
系统包括几个知识库以及网页预处理、规则学习和信息抽取三个子模块,分别从语义内容表示、逻辑结构、规则生成以及抽取结果四个层面对web页面进行描述。 |
| 7. | Multi - rules neural network learning part decreases the dimensions of attribute collection , to reach the goal of simplifying the input ; we stress the multi - rules learning algorithm based on fuzzy entropy rule ; at the same time , all the knowledge available is used to design the input layer , hidden layer and output layer of the neural network
多准则神经网络部分对客户属性集进行维数约简，重点介绍了以模糊熵准则为基础的多准则学习方法，同时提出了网络输入层、隐含层及输出层的构造方法。 |
