%0 Conference Paper %1 Cai_2021 %A Cai, Wanling %A Jin, Yucheng %A Chen, Li %B 26th International Conference on Intelligent User Interfaces %D 2021 %I ACM %K conversational-recommender critique information-exploration interactive-recommender iui2021 %P 480-490 %R 10.1145/3397481.3450657 %T Critiquing for Music Exploration in Conversational Recommender Systems %U https://doi.org/10.1145%2F3397481.3450657 %X Dialogue-based conversational recommender systems allow users to give language-based feedback on the recommended item, which has great potential for supporting users to explore the space of recommendations through conversation. In this work, we consider incorporating critiquing techniques into conversational systems to facilitate users’ exploration of music recommendations. Thus, we have developed a music chatbot with three system variants, which are respectively featured with three different critiquing techniques, i.e., user-initiated critiquing (UC), progressive system-suggested critiquing (Progressive SC), and cascading system-suggested critiquing (Cascading SC). We conducted a between-subject study (N=107) to compare these three types of systems with regards to music exploration in terms of user perception and user interaction. Results show that both UC and SC are useful for music exploration, while users perceive higher diversity of recommendations with the system that offers Cascading SC and perceive more serendipitous with the system that offers Progressive SC. In addition, we find that the critiquing techniques significantly moderate the relationships between some interaction metrics (e.g., number of listened songs, number of dialogue turns) and users’ perceived helpfulness and serendipity during music exploration.

@inproceedings{Cai_2021, abstract = {Dialogue-based conversational recommender systems allow users to give language-based feedback on the recommended item, which has great potential for supporting users to explore the space of recommendations through conversation. In this work, we consider incorporating critiquing techniques into conversational systems to facilitate users’ exploration of music recommendations. Thus, we have developed a music chatbot with three system variants, which are respectively featured with three different critiquing techniques, i.e., user-initiated critiquing (UC), progressive system-suggested critiquing (Progressive SC), and cascading system-suggested critiquing (Cascading SC). We conducted a between-subject study (N=107) to compare these three types of systems with regards to music exploration in terms of user perception and user interaction. Results show that both UC and SC are useful for music exploration, while users perceive higher diversity of recommendations with the system that offers Cascading SC and perceive more serendipitous with the system that offers Progressive SC. In addition, we find that the critiquing techniques significantly moderate the relationships between some interaction metrics (e.g., number of listened songs, number of dialogue turns) and users’ perceived helpfulness and serendipity during music exploration.}, added-at = {2022-01-16T21:07:14.000+0100}, author = {Cai, Wanling and Jin, Yucheng and Chen, Li}, biburl = {https://www.bibsonomy.org/bibtex/21b18e98b48746c93a7a16d91690c6e7c/brusilovsky}, booktitle = {26th International Conference on Intelligent User Interfaces}, description = {Critiquing for Music Exploration in Conversational Recommender Systems | 26th International Conference on Intelligent User Interfaces}, doi = {10.1145/3397481.3450657}, interhash = {67f661e0a696668a221551edceb8c360}, intrahash = {1b18e98b48746c93a7a16d91690c6e7c}, keywords = {conversational-recommender critique information-exploration interactive-recommender iui2021}, month = apr, pages = {480-490}, publisher = {{ACM}}, timestamp = {2022-01-16T21:08:39.000+0100}, title = {Critiquing for Music Exploration in Conversational Recommender Systems}, url = {https://doi.org/10.1145%2F3397481.3450657}, year = 2021 }