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, complimentarity 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.
%0 Conference Paper
%1 Ceroni:2014:BTC:2600428.2609526
%A Ceroni, Andrea
%A Tran, Nam Khanh
%A Kanhabua, Nattiya
%A Niederée, Claudia
%B Proceedings of the 37th International ACM SIGIR Conference on Research &\#38; Development in Information Retrieval
%C New York, NY, USA
%D 2014
%I ACM
%K alexandria
%P 1127--1130
%R 10.1145/2600428.2609526
%T Bridging Temporal Context Gaps Using Time-aware Re-contextualization
%U http://doi.acm.org/10.1145/2600428.2609526
%X 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, complimentarity 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.
%@ 978-1-4503-2257-7
@inproceedings{Ceroni:2014:BTC:2600428.2609526,
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, complimentarity 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.},
acmid = {2609526},
added-at = {2016-10-18T15:06:14.000+0200},
address = {New York, NY, USA},
author = {Ceroni, Andrea and Tran, Nam Khanh and Kanhabua, Nattiya and Nieder{\'e}e, Claudia},
biburl = {https://www.bibsonomy.org/bibtex/2af9def2b2f9cfd576c01bb947f3160a9/alexandriaproj},
booktitle = {Proceedings of the 37th International ACM SIGIR Conference on Research \&\#38; Development in Information Retrieval},
doi = {10.1145/2600428.2609526},
interhash = {723a7cee79d0b934e1339a307f750e42},
intrahash = {af9def2b2f9cfd576c01bb947f3160a9},
isbn = {978-1-4503-2257-7},
keywords = {alexandria},
location = {Gold Coast, Queensland, Australia},
numpages = {4},
pages = {1127--1130},
publisher = {ACM},
series = {SIGIR '14},
timestamp = {2016-10-18T15:06:14.000+0200},
title = {Bridging Temporal Context Gaps Using Time-aware Re-contextualization},
url = {http://doi.acm.org/10.1145/2600428.2609526},
year = 2014
}