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cs.IR2022
Learning to Rank from Relevance Judgments Distributions
Alberto Purpura, Gianmaria Silvello, Gian Antonio Susto
Learning to Rank (LETOR) algorithms are usually trained on annotated corpora where a single relevance label is assigned to each available document-topic pair. Within the Cranfield…
cs.IR2021
Neural Feature Selection for Learning to Rank
Alberto Purpura, Karolina Buchner, Gianmaria Silvello +1
LEarning TO Rank (LETOR) is a research area in the field of Information Retrieval (IR) where machine learning models are employed to rank a set of items. In the past few years, neu…