TY - GEN
T1 - EKNOT
T2 - 30th AAAI Conference on Artificial Intelligence, AAAI 2016
AU - Li, Min
AU - Wang, Jingjing
AU - Tong, Wenzhu
AU - Yu, Hongkun
AU - Ma, Xiuli
AU - Chen, Yucheng
AU - Cai, Haoyan
AU - Han, Jiawei
N1 - Funding Information:
UIUC. Xiuli Ma is supported by the National Natural Science Foundation of China under Grant No.61103025 and China Scholarship Council
Publisher Copyright:
© Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2016
Y1 - 2016
N2 - We present the EKNOT system that automatically discovers major events from online news articles, connects each event to its discussion in Twitter, and provides a comprehensive summary of the events from both news media and social media's point of view. EKNOT takes a time period as input and outputs a complete picture of the events within the given time range along with the public opinions. For each event, EKNOT provides multi-dimensional summaries: A) a summary from news for an objective description; b) a summary from tweets containing opinions/sentiments; c) an entity graph which illustrates the major players involved and their correlations; d) the time span of the event; and e) an opinion (sentiment) distribution. Also, if a user is interested in a particular event, he/she can zoom into this event to investigate its aspects (subevents) summarized in the same manner. EKNOT is built on real-time crawled news articles and tweets, allowing users to explore the dynamics of major events with minimal delays.
AB - We present the EKNOT system that automatically discovers major events from online news articles, connects each event to its discussion in Twitter, and provides a comprehensive summary of the events from both news media and social media's point of view. EKNOT takes a time period as input and outputs a complete picture of the events within the given time range along with the public opinions. For each event, EKNOT provides multi-dimensional summaries: A) a summary from news for an objective description; b) a summary from tweets containing opinions/sentiments; c) an entity graph which illustrates the major players involved and their correlations; d) the time span of the event; and e) an opinion (sentiment) distribution. Also, if a user is interested in a particular event, he/she can zoom into this event to investigate its aspects (subevents) summarized in the same manner. EKNOT is built on real-time crawled news articles and tweets, allowing users to explore the dynamics of major events with minimal delays.
UR - http://www.scopus.com/inward/record.url?scp=85007236055&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85007236055&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85007236055
T3 - 30th AAAI Conference on Artificial Intelligence, AAAI 2016
SP - 4367
EP - 4368
BT - 30th AAAI Conference on Artificial Intelligence, AAAI 2016
PB - American Association for Artificial Intelligence (AAAI) Press
Y2 - 12 February 2016 through 17 February 2016
ER -