cold-start problem

Alimama Tech

Apr 6, 2022 · Artificial Intelligence

Alibaba's Five Papers Accepted at SIGIR 2022

Alibaba’s research team had five papers accepted at the prestigious SIGIR 2022 conference in Madrid, covering innovations such as joint ad‑ranking and creative selection, personalized bundle generation, calibrated neural predictions, disentangled counterfactual regression, and cold‑start user recommendation, showcasing strong expertise in information retrieval and online advertising.

Recommendation systemsSIGIR 2022calibration

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Alibaba's Five Papers Accepted at SIGIR 2022

Alimama Tech

Aug 25, 2021 · Artificial Intelligence

Advertising Creative Optimization Using Hybrid Bandit Models

The article describes Alibaba Moments’ advertising creative optimization platform, which uses hybrid bandit models that combine visual‑aware ranking priors with exploration‑exploitation algorithms such as Thompson Sampling and LinUCB to dynamically select whole creatives or individual elements, improving click‑through rates and mitigating cold‑start challenges.

Algorithmic OptimizationHybrid Modelsadvertising creatives

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Advertising Creative Optimization Using Hybrid Bandit Models

NetEase Media Technology Team

Apr 4, 2019 · Artificial Intelligence

Video Recommendation System: Framework, Topic Clustering, and Related Video Retrieval

The paper proposes a video recommendation framework that combines recall and ranking modules, using a multi‑modal topic clustering approach—integrating audio, visual, and textual features via NeXtVLAD, PCA, and K‑Means—to generate unified video representations, improve candidate selection, and boost click‑through and viewing time, while addressing cold‑start and semantic relevance challenges.

A/B TestingNeXtVLADcold-start problem

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Video Recommendation System: Framework, Topic Clustering, and Related Video Retrieval