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How do recommendation models amplify popularity bias? An analysis from the spectral perspective
Recommendation Systems (RS) are often plagued by popularity bias. When training a
recommendation model on a typically long-tailed dataset, the model tends to not only inherit …
recommendation model on a typically long-tailed dataset, the model tends to not only inherit …
Modeling item exposure and user satisfaction for debiased recommendation with causal inference
Recommender systems (RSs) aim to provide suggestions for items that are most pertinent to
a particular user. Typically, RSs are trained and evaluated directly on the observed items …
a particular user. Typically, RSs are trained and evaluated directly on the observed items …
Exploiting multiple influence pattern of event organizer for event recommendation
X Han, X Meng, Y Zhang - Information Processing & Management, 2025 - Elsevier
Existing event recommendation methods pay attention to contextual factors to approach
sparse and cold-start problem, in which organizer influence is a vital factor in Event-based …
sparse and cold-start problem, in which organizer influence is a vital factor in Event-based …
Headache to Overstock? Promoting Long-tail Items through Debiased Product Bundling
Product bundling aims to organize a set of thematically related items into a combined bundle
for shipment facilitation and item promotion. To increase the exposure of fresh or …
for shipment facilitation and item promotion. To increase the exposure of fresh or …