Paper Info
Title
Detecting New and Emerging Events from Textual Sources
Abstract
Recognizing new and emerging events in a stream of news documents requires understanding the semantic structure of news reported in natural language. New event detection (NED) is the task of recognizing when a news document discusses a completely novel event. To be successful at this task, we argue a NED method must extract and represent the type of event and its participants as well as the temporal and spatial properties of the event. Our NED methods produce a 25% cost reduction over a bag-of-words baseline and a 13% cost reduction over an existing state-of-the-art approach. Additionally, we discuss our method for recognizing emerging events: the tracking and categorization of unexpected or novel events.
Year
DOI
Venue
2011
10.1109/ICSC.2011.60
ICSC
Keywords
Field
DocType
textual sources,bag-of-words baseline,cost reduction,spatial property,ned method,emerging events,new event detection,detecting new,news document,natural language,existing state-of-the-art approach,semantic structure,novel event,grounding,robustness,text analysis,measurement,semantics,spatial reasoning
Data mining,Categorization,Spatial intelligence,Computer science,Robustness (computer science),Natural language,Artificial intelligence,Natural language processing,Cost reduction,Semantics
Conference
ISSN
Citations 
PageRank 
2325-6516
0
0.34
References 
Authors
17
2
Name
Order
Citations
PageRank
Kirk Roberts133439.86
Sanda Harabagiu22203221.65