Details
| Original language | English |
|---|---|
| Title of host publication | WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web |
| Pages | 281-284 |
| Number of pages | 4 |
| Publication status | Published - 13 May 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
Wikipedia is a free multilingual online encyclopedia cover- ing a wide range of general and specific knowledge. Its con- tent is continuously maintained up-to-date and extended by a supporting community. In many cases, real-world events inuence the collaborative editing of Wikipedia articles of the involved or affected entities. In this paper, we present Wikipedia Event Reporter, a web-based system that sup- ports the entity-centric, temporal analytics of event-related information in Wikipedia by analyzing the whole history of article updates. For a given entity, the system first identifies peaks of update activities for the entity using burst detec- tion and automatically extracts event-related updates using a machine-learning approach. Further, the system deter- mines distinct events through the clustering of updates by exploiting different types of information such as update time, textual similarity, and the position of the updates within an article. Finally, the system generates the meaningful tem- poral summarization of event-related updates and automat- ically annotates the identified events in a timeline.
Keywords
- Entity timeline, Event detection, Tem- poral summarization, Wikipedia updates
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. 281-284 (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 - Temporal Summarization of Event-Related Updates in Wikipedia
AU - Georgescu, Mihai
AU - Pham, Dang Duc
AU - Kanhabua, Nattiya
AU - Zerr, Sergej
AU - Siersdorfer, Stefan
AU - Nejdl, Wolfgang
N1 - Conference code: 22
PY - 2013/5/13
Y1 - 2013/5/13
N2 - Wikipedia is a free multilingual online encyclopedia cover- ing a wide range of general and specific knowledge. Its con- tent is continuously maintained up-to-date and extended by a supporting community. In many cases, real-world events inuence the collaborative editing of Wikipedia articles of the involved or affected entities. In this paper, we present Wikipedia Event Reporter, a web-based system that sup- ports the entity-centric, temporal analytics of event-related information in Wikipedia by analyzing the whole history of article updates. For a given entity, the system first identifies peaks of update activities for the entity using burst detec- tion and automatically extracts event-related updates using a machine-learning approach. Further, the system deter- mines distinct events through the clustering of updates by exploiting different types of information such as update time, textual similarity, and the position of the updates within an article. Finally, the system generates the meaningful tem- poral summarization of event-related updates and automat- ically annotates the identified events in a timeline.
AB - Wikipedia is a free multilingual online encyclopedia cover- ing a wide range of general and specific knowledge. Its con- tent is continuously maintained up-to-date and extended by a supporting community. In many cases, real-world events inuence the collaborative editing of Wikipedia articles of the involved or affected entities. In this paper, we present Wikipedia Event Reporter, a web-based system that sup- ports the entity-centric, temporal analytics of event-related information in Wikipedia by analyzing the whole history of article updates. For a given entity, the system first identifies peaks of update activities for the entity using burst detec- tion and automatically extracts event-related updates using a machine-learning approach. Further, the system deter- mines distinct events through the clustering of updates by exploiting different types of information such as update time, textual similarity, and the position of the updates within an article. Finally, the system generates the meaningful tem- poral summarization of event-related updates and automat- ically annotates the identified events in a timeline.
KW - Entity timeline
KW - Event detection
KW - Tem- poral summarization
KW - Wikipedia updates
UR - http://www.scopus.com/inward/record.url?scp=84893045478&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84893045478
SN - 9781450320382
T3 - WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web
SP - 281
EP - 284
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 -