@inproceedings{61ef396332a2462c90611c367771ecf5,
title = "NERank: Ranking Named Entities in Document Collections",
abstract = "While most of the entity ranking research focuses on Web corpora with user queries as input, little has been done to rank entities directly from documents. We propose a ranking algorithm NERank to address this issue. NERank employs a random walk process on a weighted tripartite graph mined from the document collection. We evaluate NERank over real-life document datasets and compare it with baselines. Experimental results show the effectiveness of our method.",
keywords = "entity ranking, random walk, tripartite graph",
author = "Chengyu Wang and Rong Zhang and Xiaofeng He and Aoying Zhou",
note = "Publisher Copyright: {\textcopyright} 2016 owner/author(s).; 25th International Conference on World Wide Web, WWW 2016 ; Conference date: 11-05-2016 Through 15-05-2016",
year = "2016",
month = apr,
day = "11",
doi = "10.1145/2872518.2889348",
language = "英语",
series = "WWW 2016 Companion - Proceedings of the 25th International Conference on World Wide Web",
publisher = "Association for Computing Machinery, Inc",
pages = "123--124",
booktitle = "WWW 2016 Companion - Proceedings of the 25th International Conference on World Wide Web",
}