基于组合特征的Web人名消歧方法  

Web Name Disambiguation Approach Based on Combined Features

作　　者：辛涛 程绍银[1] 蒋凡[1] 

机构地区：[1]中国科学技术大学计算机学院

出　　处：《计算机系统应用》2015年第11期162-166,共5页Computer Systems & Applications

摘　　要：重名问题在Web人物搜索过程中是很普遍的现象.研究了Web人名消歧相关问题,提取与待消歧人名相关的不同特征集,运用向量空间模型构造人物实体的组合特征,最后通过层次聚类算法将相似度高的文档优先聚类,由此实现人名消歧.在WePS数据集上的实验结果表明,提出的方法具有良好的消歧效果.Name ambiguity is a common phenomenon when one flies to search for someone＇s mtormauon in me interact. In this paper, we have studied the web name disambiguation issue in detail. After extracting different features related to the name and then creating combined features by vector space model, we give priority to cluster the documents with high similarity by hierarchical clustering algorithm. Evaluated on the WePS data set, the proposed method showed its effectiveness in solving name disambiguation problem.

关 键 词：重名问题 人名消歧 特征提取 组合特征 层次聚类 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]