Ranking-constraint counterfactual explanation for sequential recommendation requires query-limited search to decide where to edit and what to substitute—the bottlenecked for query efficiency lies more in how the search space is structured than in the mutation rate alone. We propose TRACE (Targeted Ranking-Aware Counter...
Ungsik Kim, Sang-Min Choi, Gun-Woo Kim et al.· Proceedings of the 20th ACM...· 1 citation
Results indicate that explicitly using the missingness mask in the restoration process can improve numerical imputation performance while also preserving information useful for downstream prediction under missing-data settings relevant to predictive maintenance.
Juyoung Kim, Ji-hong Park, Sang-Min Choi et al.· IEEE Access· 0 citations
Sequential recommendation (SR) aims to predict a user’s next interaction by modeling temporal dependencies in historical behavior sequences. However, modeling long sequences introduces two challenges: longer histories often include noisy interactions irrelevant to a user’s core interests, and increasing sequence length...
Woo-Seung Kang, Minje Kim, Suwon Lee et al.· Proceedings of the 20th ACM...· 0 citations
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