Details
| Original language | English |
|---|---|
| Title of host publication | SIGIR 2014 |
| Subtitle of host publication | Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 1127-1130 |
| Number of pages | 4 |
| ISBN (print) | 9781450322591 |
| Publication status | Published - Jul 2014 |
| Event | 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2014 - Gold Coast, QLD, Australia Duration: 6 Jul 2014 → 11 Jul 2014 |
Publication series
| Name | SIGIR 2014 - Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval |
|---|
Abstract
Understanding a text, which was written some time ago, can be compared to translating a text from another language. Complete interpretation requires a mapping, in this case, a kind of time-travel translation between present context knowledge and context knowledge at time of text creation. In this paper, we study time-aware re-contextualization, the challenging problem of retrieving concise and complementing information in order to bridge this temporal context gap. We propose an approach based on learning to rank techniques using sentence-level context information extracted from Wikipedia. The employed ranking combines relevance, complementarity and time-awareness. The effectiveness of the approach is evaluated by contextualizing articles from a news archive collection using more than 7,000 manually judged relevance pairs. To this end, we show that our approach is able to retrieve a significant number of relevant context information for a given news article.
Keywords
- Complementarity, Temporal context, Time-aware re-contextualization, Wikipedia
ASJC Scopus subject areas
- Computer Science(all)
- Computer Graphics and Computer-Aided Design
- Computer Science(all)
- Information Systems
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SIGIR 2014 : Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery (ACM), 2014. p. 1127-1130 (SIGIR 2014 - Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Bridging temporal context gaps using time-aware re-contextualization
AU - Ceroni, Andrea
AU - Tran, Nam Khanh
AU - Kanhabua, Nattiya
AU - Niederée, Claudia
PY - 2014/7
Y1 - 2014/7
N2 - Understanding a text, which was written some time ago, can be compared to translating a text from another language. Complete interpretation requires a mapping, in this case, a kind of time-travel translation between present context knowledge and context knowledge at time of text creation. In this paper, we study time-aware re-contextualization, the challenging problem of retrieving concise and complementing information in order to bridge this temporal context gap. We propose an approach based on learning to rank techniques using sentence-level context information extracted from Wikipedia. The employed ranking combines relevance, complementarity and time-awareness. The effectiveness of the approach is evaluated by contextualizing articles from a news archive collection using more than 7,000 manually judged relevance pairs. To this end, we show that our approach is able to retrieve a significant number of relevant context information for a given news article.
AB - Understanding a text, which was written some time ago, can be compared to translating a text from another language. Complete interpretation requires a mapping, in this case, a kind of time-travel translation between present context knowledge and context knowledge at time of text creation. In this paper, we study time-aware re-contextualization, the challenging problem of retrieving concise and complementing information in order to bridge this temporal context gap. We propose an approach based on learning to rank techniques using sentence-level context information extracted from Wikipedia. The employed ranking combines relevance, complementarity and time-awareness. The effectiveness of the approach is evaluated by contextualizing articles from a news archive collection using more than 7,000 manually judged relevance pairs. To this end, we show that our approach is able to retrieve a significant number of relevant context information for a given news article.
KW - Complementarity
KW - Temporal context
KW - Time-aware re-contextualization
KW - Wikipedia
UR - http://www.scopus.com/inward/record.url?scp=84904539716&partnerID=8YFLogxK
U2 - 10.1145/2600428.2609526
DO - 10.1145/2600428.2609526
M3 - Conference contribution
AN - SCOPUS:84904539716
SN - 9781450322591
T3 - SIGIR 2014 - Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval
SP - 1127
EP - 1130
BT - SIGIR 2014
PB - Association for Computing Machinery (ACM)
T2 - 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2014
Y2 - 6 July 2014 through 11 July 2014
ER -