A unified framework for name disambiguation

Name ambiguity problem has been a challenging issue for a long history. In this paper, we intend to make a thorough investigation of the whole problem. Specifically, we formalize the name disambiguation problem in a unified framework. The framework can incorporate both attribute and relationship into a probabilistic model. We explore a dynamic approach for automatically estimating the person number K and employ an adaptive distance measure to estimate the distance between objects. Experimental results show that our proposed framework can significantly outperform the baseline method. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval, Digital Libraries, I.2.6 [Artificial Intelligence]: Learning, H.2.8 [Database Management]: Database Applications. General Terms Algorithms, Experimentation Keywords Name Disambiguation, Probabilistic Model, Digital Library

• Type: Conference
• Year: 2008
• Where: WWW
• Authors: Jie Tang, Jing Zhang, Duo Zhang, Juanzi Li
• Keywords: Disambiguation Problem, Internet Technology, Keywords Name Disambiguation, Name Ambiguity Problem, WWW 2008