Title :
Event graph model and its properties: A method of mining trends in text streams
Author :
Zhao, Chengli ; Zhang, Xue
Author_Institution :
Dept. of Mathematic & Syst. Sci., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
Massive text stream is a very important source of information. There are rich graph structures contained in massive texts, which can be used as an effective method to mine trends embodied in the contents in text streams. This paper formally defines the event graph model based on systems science theory, and discusses its properties. This model aims to extract the potential events and relationships between them from text streams.
Keywords :
data mining; graph theory; text analysis; event graph model; graph structures; mining trends; systems science theory; text streams; event; event graph; text stream;
Conference_Titel :
Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-61284-485-5
DOI :
10.1109/ICCSN.2011.6014175
