id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-132843-ilxt4b6g	Zhao, Liang	Event Prediction in the Big Data Era: A Systematic Survey	2020-07-19		.txt	text/plain	19742	1111	49	Based on large amounts of data on historical events and their potential precursors, event prediction methods typically strive to apply predictive mapping to build on these observations to predict future events, utilizing predictive analysis techniques from domains such as machine learning, data mining, pattern recognition, statistics, and other computational models [16, 26, 92] . Event prediction methods usually need to predict multiple facets of events including their time, location, topic, intensity, and duration, each of which may utilize a different data structure [171] . Existing event prediction methods are categorized according to their event aspects (time, location, and semantics), problem formulation, and corresponding techniques to create the taxonomy of a generic framework. The second step is to identify events in the predicted future time seriesx using either unsupervised methods such as burstness detection [31] and change detection [109] , or supervised techniques based on learning event characterization function.	./cache/cord-132843-ilxt4b6g.txt	./txt/cord-132843-ilxt4b6g.txt