Details
| Original language | English |
|---|---|
| Title of host publication | WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web |
| Pages | 343-347 |
| Number of pages | 5 |
| Publication status | Published - 1 Dec 2013 |
| Event | 22nd International Conference on World Wide Web - Rio de Janeiro, Brazil Duration: 13 May 2013 → 17 May 2013 Conference number: 22 |
Publication series
| Name | WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web |
|---|
Abstract
Helping users to understand the news is an acute problem nowadays as the users are struggling to keep up with tremendous amount of information published every day in the Internet. In this research, we focus on modelling the content of news events by their semantic relations with other events, and generating structured summarization.
Keywords
- Causal, Hierarchical, News events, Relation extraction, Spatial, Structured summarization, Temporal
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
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WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web. 2013. p. 343-347 (WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Structured summarization for news events
AU - Tran, Giang Binh
N1 - Conference code: 22
PY - 2013/12/1
Y1 - 2013/12/1
N2 - Helping users to understand the news is an acute problem nowadays as the users are struggling to keep up with tremendous amount of information published every day in the Internet. In this research, we focus on modelling the content of news events by their semantic relations with other events, and generating structured summarization.
AB - Helping users to understand the news is an acute problem nowadays as the users are struggling to keep up with tremendous amount of information published every day in the Internet. In this research, we focus on modelling the content of news events by their semantic relations with other events, and generating structured summarization.
KW - Causal
KW - Hierarchical
KW - News events
KW - Relation extraction
KW - Spatial
KW - Structured summarization
KW - Temporal
UR - http://www.scopus.com/inward/record.url?scp=84893142680&partnerID=8YFLogxK
U2 - https://doi.org/10.1145/2487788.2487940
DO - https://doi.org/10.1145/2487788.2487940
M3 - Conference contribution
AN - SCOPUS:84893142680
SN - 9781450320382
T3 - WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web
SP - 343
EP - 347
BT - WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web
T2 - 22nd International Conference on World Wide Web
Y2 - 13 May 2013 through 17 May 2013
ER -