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pro vyhledávání: '"Croft W"'
Autor:
Hashemi, Helia, Zhuang, Yong, Kothur, Sachith Sri Ram, Prasad, Srivas, Meij, Edgar, Croft, W. Bruce
In information retrieval (IR), domain adaptation is the process of adapting a retrieval model to a new domain whose data distribution is different from the source domain. Existing methods in this area focus on unsupervised domain adaptation where the
Externí odkaz:
http://arxiv.org/abs/2307.02740
Neural ranking models (NRMs) have demonstrated effective performance in several information retrieval (IR) tasks. However, training NRMs often requires large-scale training data, which is difficult and expensive to obtain. To address this issue, one
Externí odkaz:
http://arxiv.org/abs/2304.08912
Autor:
Croft, W.1 (AUTHOR) w.d.croft@bham.ac.uk, Pounds, R.2,3 (AUTHOR), Jeevan, D.2 (AUTHOR), Singh, K.3 (AUTHOR), Balega, J.3 (AUTHOR), Sundar, S.2,3 (AUTHOR), Williams, A.4 (AUTHOR), Ganesan, R.2,4 (AUTHOR), Kehoe, S.5 (AUTHOR), Ott, S.6 (AUTHOR), Zuo, J.1 (AUTHOR), Yap, J.2,3 (AUTHOR), Moss, P.1,7,8 (AUTHOR) p.moss@bham.ac.uk
Publikováno v:
Communications Biology. 9/28/2024, Vol. 7 Issue 1, p1-12. 12p.
Existing commercial search engines often struggle to represent different perspectives of a search query. Argument retrieval systems address this limitation of search engines and provide both positive (PRO) and negative (CON) perspectives about a user
Externí odkaz:
http://arxiv.org/abs/2108.10442