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pro vyhledávání: '"Pobrotyn, Przemys��aw"'
Learning to Rank (LTR) algorithms are usually evaluated using Information Retrieval metrics like Normalised Discounted Cumulative Gain (NDCG) or Mean Average Precision. As these metrics rely on sorting predicted items' scores (and thus, on items' ran
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8af5f33775373b1c7365f7e9913c1a7f
http://arxiv.org/abs/2102.07831
http://arxiv.org/abs/2102.07831
Autor:
Pobrotyn, Przemys��aw, Bartczak, Tomasz, Synowiec, Miko��aj, Bia��obrzeski, Rados��aw, Bojar, Jaros��aw
Learning to rank is a key component of many e-commerce search engines. In learning to rank, one is interested in optimising the global ordering of a list of items according to their utility for users.Popular approaches learn a scoring function that s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dcb94e3873c7e8a8647c4fd001019de6
http://arxiv.org/abs/2005.10084
http://arxiv.org/abs/2005.10084