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pro vyhledávání: '"Busolin, Francesco"'
Autor:
Busolin, Francesco, Lucchese, Claudio, Nardini, Franco Maria, Orlando, Salvatore, Perego, Raffaele, Trani, Salvatore
Learned dense representations are a popular family of techniques for encoding queries and documents using high-dimensional embeddings, which enable retrieval by performing approximate k nearest-neighbors search (A-kNN). A popular technique for making
Externí odkaz:
http://arxiv.org/abs/2408.04981
Autor:
Busolin, Francesco, Lucchese, Claudio, Nardini, Franco Maria, Orlando, Salvatore, Perego, Raffaele, Trani, Salvatore
Publikováno v:
44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Association for Computing Machinery, 2021, 2217-2221
Modern search engine ranking pipelines are commonly based on large machine-learned ensembles of regression trees. We propose LEAR, a novel - learned - technique aimed to reduce the average number of trees traversed by documents to accumulate the scor
Externí odkaz:
http://arxiv.org/abs/2105.02568
Akademický článek
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