Dataset Groups Activity Stream Customized Conversational Recommender Systems Conversational recommender systems (CRS) aim to capture user's current intentions and provide recommendations through real-time multi-turn conversational interactions. BibTex: @dataset{Shuokai_Li_and_Yongchun_Zhu_and_Ruobing_Xie_and_Zhenwei_Tang_and_Zhao_Zhang_and_Fuzhen_Zhuang_and_Qing_He_and_Hui_Xiong_2024, abstract = {Conversational recommender systems (CRS) aim to capture user's current intentions and provide recommendations through real-time multi-turn conversational interactions.}, author = {Shuokai Li and Yongchun Zhu and Ruobing Xie and Zhenwei Tang and Zhao Zhang and Fuzhen Zhuang and Qing He and Hui Xiong}, doi = {10.57702/f5zsi7pc}, institution = {No Organization}, keyword = {'Conversational Recommender Systems', 'Dialogue Generation', 'User Intentions'}, month = {dec}, publisher = {TIB}, title = {Customized Conversational Recommender Systems}, url = {https://service.tib.eu/ldmservice/dataset/customized-conversational-recommender-systems}, year = {2024} }
