Computing Terms Semantic Relatedness by Knowledge in Wikipedia

摘要：

　　Many researchers have recognized Wikipedia as a resource of huge dynamic knowledge base in recent years.This paper provides a new approach for obtaining measures of terms semantic relatedness, which maps terms to relevant Wikipedia articles as the background information for analyzing.The proposed algorithm WLA focuses on the hyperlink structure and summary paragraph extracted from the topic pages to compute two terms similarity.Comparing with other similar techniques,the approach is less computationally intensive, because only the first paragraph is analyzed, not the entire text.Our method achieves good performance on the widely used test set WS-353.

关键词： Wikipedia link structure semantic relatedness

作者: Dexin Zhao Liangliang Qin Pengjie Liu Zhen Ma Yukun Li

作者单位: Tianjin Key Laboratory of Intelligent Computing and Novel Software Technology, Tianjin University of Tianjin Keyilong Decoration Engineering Co., Ltd., Tianjin 300202, China

会议类型: 国际会议

会议名称: The 12th Web Information System and Application Conference第十二届全国Web信息系统及其应用学术会议(WISA2015)、全国第十次语义Web 与本体论学术研讨会(SWON2015)、全国第九次电子政务技术及应用学术研讨会(EGTA2015)

会议地点: 济南

会议语种:英文

页码: 107-111

在线出版日期: 2015-09-11（万方平台首次上网日期，不代表论文的发表时间）