A Unified Probabilistic Framework for Name Disambiguation in Digital Library
A Unified Probabilistic Framework for Name Disambiguation in Digital Library
复制标题
数字图书馆名称消歧的统一概率框架
DOI：
10.1109/tkde.2011.13
复制
发表时间：
2012-06-01
影响因子：
8.9
通讯作者：
Zhang, Jing
中科院分区：
文献类型：
--
作者：
Tang, Jie;Fong, A. C. M.;Zhang, Jing
尽管经过多年的研究，名称模糊的问题在很大程度上仍然没有得到解决。突出的问题包括如何在一个统一的方法中捕获所有的信息用于姓名消歧，以及如何确定消歧过程中的人数K。在本文中，我们正式的问题，在一个统一的概率框架，其中包括属性和关系。具体来说，我们定义了一个消歧的目标函数的问题，并提出了一个两步参数估计算法。我们还研究了一个动态的方法来估计人数K。实验表明，我们提出的框架显着优于四个基线方法使用聚类算法和其他两个以前的方法。实验结果表明，该方法自动求出的K值与实际值接近。
Despite years of research, the name ambiguity problem remains largely unresolved. Outstanding issues include how to capture all information for name disambiguation in a unified approach, and how to determine the number of people K in the disambiguation process. In this paper, we formalize the problem in a unified probabilistic framework, which incorporates both attributes and relationships. Specifically, we define a disambiguation objective function for the problem and propose a two-step parameter estimation algorithm. We also investigate a dynamic approach for estimating the number of people K. Experiments show that our proposed framework significantly outperforms four baseline methods of using clustering algorithms and two other previous methods. Experiments also indicate that the number K automatically found by our method is close to the actual number.