论文标题
IITD-DBAI：具有伪交易的反馈和查询重新制定的多阶段检索
IITD-DBAI: Multi-Stage Retrieval with Pseudo-Relevance Feedback and Query Reformulation
论文作者
论文摘要
解决上下文依赖性是对话系统中最具挑战性的任务之一。我们提交给Cast-2021的提交旨在在随后的所有转弯中保留关键术语和上下文，并使用经典信息检索方法。它的目的是从语料库中提取尽可能的相关文件。我们参加了自动轨道，并在Cast-2021中提交了两次跑步。我们的提交产生了平均NDCG@3性能比中位模型更好。
Resolving the contextual dependency is one of the most challenging tasks in the Conversational system. Our submission to CAsT-2021 aimed to preserve the key terms and the context in all subsequent turns and use classical Information retrieval methods. It was aimed to pull as relevant documents as possible from the corpus. We have participated in automatic track and submitted two runs in the CAsT-2021. Our submission has produced a mean NDCG@3 performance better than the median model.
