Research Paper on Audience Expansion Model Accepted at ACM SIGIR 2024


Congratulations to Md Mostafizur Rahman, Daisuke Kikuta (Ex-intern, RIT), Yu Hirate, Researchers at Rakuten Institute of Technology in Tokyo, along with Toyotaro Suzumura, collaborator from the University of Tokyo, on the acceptance of their paper at the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval for presentation. Their paper, titled “Graph-Based Audience Expansion Model for Marketing Campaigns,” introduces AudienceLinkNet, a novel solution for audience expansion in the context of Rakuten’s diverse services and clients. AudienceLinkNet tackles challenges such as a heterogeneous user base, complex marketing campaigns, and limited seed users by formulating the audience expansion problem as a graph problem and combining the Pre-trained Knowledge Graph Embedding Model with Graph Convolutional Networks.

Don’t miss the chance to catch their presentation at the 47th International ACM SIGIR Conference, happening on July 14-18, 2024, in Washington D.C., USA.

Copied! instagram