@inproceedings{da8d0b36d98a4fe0b994ba58f7dcbe41,
title = "Scalable spatio-temporal knowledge harvesting",
abstract = "Knowledge harvesting enables the automated construction of large knowledge bases. In this work, we made a first attempt to harvest spatio-temporal knowledge from news archives to construct trajectories of individual entities for spatio-temporal entity tracking. Our approach consists of an entity extraction and disambiguation module and a fact generation module which produce pertinent trajectory records from textual sources. The evaluation on the 20 years' New York Times news article corpus showed that our methods are effective and scalable.",
keywords = "entity disambiguation, knowledge harvesting, mapreduce, news archive, spatio-temporal facts",
author = "Yafang Wang and Bin Yang and Spyros Zoupanos and Marc Spaniol and Gerhard Weikum",
year = "2011",
doi = "10.1145/1963192.1963265",
language = "英语",
isbn = "9781450305181",
series = "Proceedings of the 20th International Conference Companion on World Wide Web, WWW 2011",
pages = "143--144",
booktitle = "Proceedings of the 20th International Conference Companion on World Wide Web, WWW 2011",
note = "20th International Conference Companion on World Wide Web, WWW 2011 ; Conference date: 28-03-2011 Through 01-04-2011",
}