Paper: Using Names And Topics For New Event Detection

ACL ID H05-1016
Title Using Names And Topics For New Event Detection
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2005
Authors

New Event Detection (NED) involves monitoring chronologically-ordered news streams to automatically detect the stories that report on new events. We compare two stories by finding three cosine simi- larities based on names, topics and the full text. These additional comparisons sug- gest treating the NED problem as a bi- nary classification problem with the com- parison scores serving as features. The classifier models we learned show statis- tically significant improvement over the baseline vector space model system on all the collections we tested, including the lat- est TDT5 collection. The presence of automatic speech recog- nizer (ASR) output of broadcast news in news streams can reduce performance and render our named entity recognition based approaches ineffective. We provide a so- ...