Dataset Groups Activity Stream GroupIM: A Mutual Information Maximization Framework for Neural Group Recommendation We study the problem of making item recommendations to ephemeral groups, which comprise users who purchase very few (or no) items together. BibTex: @dataset{Aravind_Sankar_and_Yanhong_Wu_and_Yuhang_Wu_and_Wei_Zhang_and_Hao_Yang_and_Hari_Sundaram_2024, abstract = {We study the problem of making item recommendations to ephemeral groups, which comprise users who purchase very few (or no) items together.}, author = {Aravind Sankar and Yanhong Wu and Yuhang Wu and Wei Zhang and Hao Yang and Hari Sundaram}, doi = {10.57702/pwqsmvn5}, institution = {No Organization}, keyword = {'ephemeral groups', 'item recommendations', 'mutual information', 'neural collaborative filtering', 'representation learning'}, month = {dec}, publisher = {TIB}, title = {GroupIM: A Mutual Information Maximization Framework for Neural Group Recommendation}, url = {https://service.tib.eu/ldmservice/dataset/groupim--a-mutual-information-maximization-framework-for-neural-group-recommendation}, year = {2024} }
