4 citations · 12 across the 9 of their papers we have counts for
10 papers
Position Bias Estimation with Item Embedding for Sparse Dataset
Shion Ishikawa, Yun Ching Liu, Young-Joo Chung +1
Estimating position bias is a well-known challenge in Learning to Rank (L2R). Click data in e-commerce applications, such as targeted advertisements and search engines, provides im…
Meta-Shop: Improving Item Advertisement For Small Businesses
Yang Shi, Guannan Liang, Young-joo Chung
In this paper, we study item advertisements for small businesses. This application recommends prospective customers to specific items requested by businesses. From analysis, we fou…
One-class Recommendation Systems with the Hinge Pairwise Distance Loss and Orthogonal Representations
Ramin Raziperchikolaei, Young-joo Chung
In one-class recommendation systems, the goal is to learn a model from a small set of interacted users and items and then identify the positively-related user-item pairs among a la…
Dynamic collaborative filtering Thompson Sampling for cross-domain advertisements recommendation
Shion Ishikawa, Young-joo Chung, Yu Hirate
Recently online advertisers utilize Recommender systems (RSs) for display advertising to improve users' engagement. The contextual bandit model is a widely used RS to exploit and e…
Learning Similarity Preserving Binary Codes for Recommender Systems
Yang Shi, Young-joo Chung
Hashing-based Recommender Systems (RSs) are widely studied to provide scalable services. The existing methods for the systems combine three modules to achieve efficiency: feature e…
Simultaneous Learning of the Inputs and Parameters in Neural Collaborative Filtering
Ramin Raziperchikolaei, Young-joo Chung
Neural network-based collaborative filtering systems focus on designing network architectures to learn better representations while fixing the input to the user/item interaction ve…
Efficient Cross-Modal Retrieval via Deep Binary Hashing and Quantization
Yang Shi, Young-joo Chung
Cross-modal retrieval aims to search for data with similar semantic meanings across different content modalities. However, cross-modal retrieval requires huge amounts of storage an…
Recommending Short-lived Dynamic Packages for Golf Booking Services
Robin Swezey, Young-joo Chung
We introduce an approach to recommending short-lived dynamic packages for golf booking services. Two challenges are addressed in this work. The first is the short life of the items…
Neural Representations in Hybrid Recommender Systems: Prediction versus Regularization
Ramin Raziperchikolaei, Tianyu Li, Young-joo Chung
Autoencoder-based hybrid recommender systems have become popular recently because of their ability to learn user and item representations by reconstructing various information sour…
JESC: Japanese-English Subtitle Corpus
Reid Pryzant, Yongjoo Chung, Dan Jurafsky +1
In this paper we describe the Japanese-English Subtitle Corpus (JESC). JESC is a large Japanese-English parallel corpus covering the underrepresented domain of conversational dialo…