Position Bias Estimation with Item Embedding for Sparse Dataset

no code implementations • 10 May 2023 • Shion Ishikawa, Yun Ching Liu, Young-joo Chung, Yu Hirate

Using a public dataset and internal carousel advertisement click dataset, we empirically show that item embedding with Latent Semantic Indexing (LSI) and Variational Auto-Encoder (VAE) improves the accuracy of position bias estimation and the estimated position bias enhances Learning to Rank performance.

Denoising Learning-To-Rank +2

Dynamic collaborative filtering Thompson Sampling for cross-domain advertisements recommendation

no code implementations • 25 Aug 2022 • Shion Ishikawa, Young-joo Chung, Yu Hirate

We first show transferring knowledge and incorporating temporal dynamics improve the performance of the baseline models on a synthetic dataset.

Collaborative Filtering Recommendation Systems +1