Conversational Search and Recommendation: Introduction to the Special Issue

While conversational search and recommendation has roots in early Information Retrieval (IR) research, the recent advances in automatic voice recognition and conversational agents have created increasing interest in this area. This topic was recognized as an emerging research area in the Third Strategic Workshop on Information Retrieval in Lorne (SWIRL 2018) [Culpepper et al. 2018]. Conversational search and recommendation systems consist of multiple components, from user modeling to conversational understanding to query modeling to result presentation. In recent years, the IR and related communities have witnessed a number of major contributions to the field of conversational search and recommendation. They include but are not limited to conversational search conceptualization (e.g., Azzopardi et al. [2018], Deldjoo et al. [2021], and Radlinski and Craswell [2017]), effective conversational query re-writing (e.g., Yu et al. [2020]), generating and selecting clarifying questions (e.g., Zamani et al. [2020a, c]), conversational preference elicitation (e.g., Radlinski et al. [2019] and Zhang et al. [2018]), and understanding user interactions with spoken conversational systems (e.g., Trippas et al. [2018, 2020]). The growing body of work in this area has been supplemented by an increasing number of recent seminars (e.g., Anand et al. [2020]), workshops (e.g., Arguello et al. [2018], Burtsev et al. [2017], Chuklin et al. [2018], and