The Construction of Visualness Attributes Network Based on Conceptual Graphs

摘要：

This paper proposed a new method for extracting visualness attributes (the extent to which an attribute can be perceived visually) that based on conceptual graphs (CGs). By providing a small scale seed attributes, this method acquire the context which contain these seed attributes by two steps, primary entity matching and sentence selection, then transform the selected sentences into CG templates, after systematic expansion of its semantic information on the basis of HowNet lexicon, extract the attribute concepts by computing the similarity between CG templates and textual CGs, then compute the visualness of these attribute concepts and retain the attributes with the visualness value greater than the threshold. At last, we construct the relationship among the attributes by bringing in world knowledge. Experiments have demonstrated the effectiveness of our conceptual graph based method when compared with the state of art ones.

关键词： Conceptual Graph (CG) HowNet Semantic Similarity Visualness Attribute Extraction

作者: Jing Yang Lei Zhangjun Feng Heng-wei Liu Jun Feng

作者单位: Department of Computer Science Northwest University Xian, China

会议类型: 国际会议

会议名称: 2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics 第4届智能人机系统与控制论国际会议 IHMSC 2012

会议地点: 南昌

会议语种:英文

页码: 590-593

在线出版日期: 2012-08-26（万方平台首次上网日期，不代表论文的发表时间）