Before revision:  To address this problem, we present an effective multi-stage pipeline for passage ranking in conversational searchthat integrates a widely-used IR system with a conversational query reformulation module. Along these lines , we propose two simple yet effective query reformulation approaches: historical query expansion (HQE) and neural transfer reformulation (NTR) . Whereas HQE applies query expansion, a traditional IR query reformulation technique, NTR transfers human knowledge of conversational query understanding to a neural query reformulation model.
After revision:  To address this problem, we present an effective multi-stage ad-hoc IR system. Specifically , we propose two simple yet effective query reformulation approaches: historical query expansion (HQE) and neural transfer reformulation (NTR) . Whereas HQE applies query expansion, a traditional IR query reformulation technique, NTR transfers human knowledge of conversational query understanding to a neural query reformulation model.