Musen Wen

According to our database, Musen Wen authored at least 8 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Enhanced E-Commerce Attribute Extraction: Innovating with Decorative Relation Correction and LLAMA 2.0-Based Annotation.

Jianghong Zhou, Weizhi Du, Md Omar Faruk Rokon, Zhaodong Wang, Jiaxuan Xu, Isha Shah, Kuang-chih Lee, Musen Wen

CoRR, 2023

Leveraging Large Language Models for Enhanced Product Descriptions in eCommerce.

Jianghong Zhou, Bo Liu, Jhalak Nilesh Acharya Yao Hong, Kuang-chih Lee, Musen Wen

CoRR, 2023

Click-Conversion Multi-Task Model with Position Bias Mitigation for Sponsored Search in eCommerce.

Yibo Wang, Yanbing Xue, Bo Liu, Musen Wen, Wenting Zhao, Stephen Guo, Philip S. Yu

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

2022

Applied Machine Learning Methods for Time Series Forecasting.

Linsey Pang, Wei Liu, Lingfei Wu, Kexin Xie, Stephen Guo, Raghav Chalapathy, Musen Wen

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2019

Practical Lessons from Predicting New User Demographics for Ad Targeting.

Musen Wen, Zhen Xia, Deepak Kumar Vasthimal

Proceedings of the 2nd Workshop on Online Recommender Systems and User Modeling, 2019

Building Large-Scale Deep Learning System for Entity Recognition in E-Commerce Search.

Musen Wen, Deepak Kumar Vasthimal, Alan Lu, Tian Wang, Aimin Guo

Proceedings of the 6th IEEE/ACM International Conference on Big Data Computing, 2019

2018

Semi-Supervised Learning with Auxiliary Evaluation Component for Large Scale e-Commerce Text Classification.

Mingkuan Liu, Musen Wen, Selçuk Köprü, Xianjing Liu, Alan Lu

Proceedings of the Workshop on Deep Learning Approaches for Low-Resource NLP, 2018

2016

A Sub-linear, Massive-scale Look-alike Audience Extension System A Massive-scale Look-alike Audience Extension.

Qiang Ma, Musen Wen, Zhen Xia, Datong Chen

Proceedings of the 5th International Workshop on Big Data, 2016