TY - GEN
T1 - Incorporating terminology evolution for query translation in text retrieval with association rules
AU - Kalurachchi, Amal
AU - Varde, Aparna S.
AU - Bedathur, Srikanta
AU - Weikum, Gerhard
AU - Peng, Jing
AU - Feldman, Anna
PY - 2010
Y1 - 2010
N2 - Time-stamped documents such as newswire articles, blog posts and other web-pages are often archived online. When these archives cover long spans of time, the terminology within them could undergo significant changes. Hence when users pose queries pertaining to historical information over such documents, the queries need to be translated taking into account these temporal changes in order to provide accurate responses to users. For example, a query on Sri Lanka should automatically retrieve documents with its former name Ceylon. We call such concepts SITACs, i.e., Semantically Identical Temporally Altering Concepts. In order to discover SITACs, we propose an approach based on a novel framework constituting an integration of natural language processing, association rule mining and contextual similarity as a learning technique. The proposed approach has been experimented with real data and has been found to yield good results with respect to efficiency and accuracy.
AB - Time-stamped documents such as newswire articles, blog posts and other web-pages are often archived online. When these archives cover long spans of time, the terminology within them could undergo significant changes. Hence when users pose queries pertaining to historical information over such documents, the queries need to be translated taking into account these temporal changes in order to provide accurate responses to users. For example, a query on Sri Lanka should automatically retrieve documents with its former name Ceylon. We call such concepts SITACs, i.e., Semantically Identical Temporally Altering Concepts. In order to discover SITACs, we propose an approach based on a novel framework constituting an integration of natural language processing, association rule mining and contextual similarity as a learning technique. The proposed approach has been experimented with real data and has been found to yield good results with respect to efficiency and accuracy.
KW - Association rules
KW - Contextual similarity
KW - Natural language processing
KW - Ranking
KW - Search
KW - Web IR
UR - http://www.scopus.com/inward/record.url?scp=78651306430&partnerID=8YFLogxK
U2 - 10.1145/1871437.1871730
DO - 10.1145/1871437.1871730
M3 - Conference contribution
AN - SCOPUS:78651306430
SN - 9781450300995
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 1789
EP - 1792
BT - CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops
T2 - 19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10
Y2 - 26 October 2010 through 30 October 2010
ER -