Dealing with Typos for BERT-based Passage Retrieval and Ranking
Shengyao Zhuang, Guido Zuccon
2021Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing35 citationsDOIOpen Access PDF
Abstract
Passage retrieval and ranking is a key task in open-domain question answering and information retrieval. Current effective approaches mostly rely on pre-trained deep language model-based retrievers and rankers. These methods have been shown to effectively model the semantic matching between queries and passages, also in presence of keyword mismatch, i.e. passages that are relevant to a query but do not contain important query keywords.
Topics & Concepts
Computer scienceRanking (information retrieval)Information retrievalContext (archaeology)Training setArtificial intelligenceMatching (statistics)Question answeringStatisticsMathematicsPaleontologyBiologyTopic ModelingNatural Language Processing TechniquesText and Document Classification Technologies