Ранжирование документов

The usefulness of a translated text for gist- ing purposes strongly depends on the over- all translation quality of the text, but espe- cially on the translation quality of the …...

In this paper we present a novel approach to automatic creation of anchor texts for hyper- links in a document pointing to similar doc- uments. Methods used in this approach …...

AbstractOrdinal regression which is known with learning to rank has long been used in information retrieval (IR). Learning to rank algorithms, have been tailored in document ranking, information filtering, and …...

AbstractThis work proposes the use of a pretrained sequence-to-sequence model for document ranking. Our approach is fundamentally different from a commonly adopted classification-based formulation based on encoder-only pretrained transformer architectures …...

AbstractThe computing cost of transformer self-attention often necessitates breaking long documents to fit in pretrained models in document ranking tasks. In this paper, we design Query-Directed Sparse attention that induces …...

AbstractDocument ranking aims at sorting a collection of documents with their relevance to a query. Contemporary methods explore more efficient transformers or divide long documents into passages to handle the …...