南京大学学报：自然科学版2012，Vol.48Issue(4)：383-389,7.
领域本体概念实例、属性和属性值的抽取及关系预测
Extraction and relation prediction of domain ontology concept instance, attribute and attribute value
摘要
Abstract
This paper studies how to use the Collaboration Classifier （Conditional Random Fields （CRFs） and Support Vector Machine （SVM）） to solve the extraction and relation prediction problem of ontology concept instance, attribute and attribute value. Firstly, taken concept instance, attribute and attribute value as three entities, the problem of extraction these three entities was converted to a named entity recognition problem, CRFs classifier model was adopted to recognize entities; Furthermore, made a definition for the relations between the concept instance, attribute and attribute value and made relations prediction among concept instance, attribute andattribute value after they were identified respectively, if there is a relationship among the concept instance, attribute and attribute value, marked 1, otherwise marked 0, then use SVM classifier model to make predictions on entity corresponding relation. Taking six trials on concept instance, attribute and attribute value on Yunnan tourist attractions for instance, the experiment is done to make that the accuracy rate of Collaborative Classifier achieves 84.4% and recall rate is up to 82.7% and the F score is 83.6% ,compared to Words Co-occurrence model, its F- score increased by 20%.关键词
领域本体/概念实例抽取/属性抽取/属性值抽取/条件随机场/支持向量机Key words
domain ontology/concept instance extraction/attribute extraction/attribute values extraction/conditional random fields/support vector machine.分类
计算机与自动化引用本文复制引用
郭剑毅,李真,余正涛,张志坤..领域本体概念实例、属性和属性值的抽取及关系预测[J].南京大学学报：自然科学版,2012,48(4):383-389,7.基金项目
国家自然科学基金（60863011）,云南省自然科学基金（2008CC023）,云南省中青年学术技术带头人后备人才项目（2007PY01-11）,云南省教育厅基金 （）
