@inproceedings{d55d85e6c69142a0ab0a05d5d78e5f4e,
title = "Event detection and recommendation based on heterogeneous information",
abstract = "Previous research on event detection only handles with text data, and there is still no agreed standard except for the reports amount on judging whether a set of information should be pushed as a hot event. In this paper, we present an event detection framework based on heterogeneous information. Firstly, the coarse classification of structured data is transplanted to text data to make the information set more precise, and then twice clustering using multi-features is attempted to enhance the performance of event detection. Meanwhile, data fluctuation of structured data is monitored to determine the event priority. The experiment results and online system proved the availability of our method.",
keywords = "Clustering, Event detection, Heterogeneous information, Multi-features",
author = "Bo Yuan and Qingcai Chen and Yang Xiang and Xiaolong Wang",
year = "2013",
doi = "10.1007/978-1-4471-4850-0\_52",
language = "英语",
isbn = "9781447148494",
series = "Lecture Notes in Electrical Engineering",
number = "VOL. 2",
pages = "407--416",
booktitle = "Proceedings of the International Conference on Information Engineering and Applications, IEA 2012",
edition = "VOL. 2",
note = "2nd International Conference on Information Engineering and Applications, IEA 2012 ; Conference date: 26-10-2012 Through 28-10-2012",
}