首页>
外国专利>
STACKED GENERALIZATION LEARNING FOR DOCUMENT ANNOTATION
STACKED GENERALIZATION LEARNING FOR DOCUMENT ANNOTATION
展开▼
机译:文献注释的广义广义学习
展开▼
页面导航
摘要
著录项
相似文献
摘要
A document annotation method includes modeling data elements of an input document and dependencies between the data elements as a dependency network. Static features of at least some of the data elements are defined, each expressing a relationship between a characteristic of the data element and its label. Dynamic features are defined which define links between an element and labels of the element and of a second element. Parameters of a collective probabilistic model for the document are learned, each expressing a conditional probability that a first data element should be labeled with information derived from a label of a neighbor data element linked to the first data element by a dynamic feature. The learning includes decomposing a globally trained model into a set of local learning models. The local learning models each employ static features to generate estimations of the neighbor element labels for at least one of the data elements.
展开▼