On-Line New Event Detection and Tracking
James W Allan, Ron Papka, Victor P. Lavrenko · ACM SIGIR Forum · 2017
We define and describe the related problems of new event detection and event tracking within a stream of broadcast news stories. We focus on a strict on-line setting---i.e., the system must make decisions about one story before looking at any subsequent stories. Our approach to detection uses a single pass clustering algorithm and a novel thresholding model that incorporates the properties of events as a major component. Our approach to tracking is similar to typical information filtering methods. We discuss the value of "surprising" features that have unusual occurrence characteristics, and briefly explore on-line adaptive filtering to handle evolving events in the news. New event detection and event tracking are part of the Topic Detection and Tracking (TDT) initiative. 1 Introduction The problems discussed in this study are new event detection and event tracking. The goal of those tasks is to monitor a stream of broadcast news stories so as to determine the relationships between ...