Search Results for author: Yunya Song

Found 5 papers, 2 papers with code

Improving Deep Embedded Clustering via Learning Cluster-level Representations

no code implementations COLING 2022 Qing Yin, Zhihua Wang, Yunya Song, Yida Xu, Shuai Niu, Liang Bai, Yike Guo, Xian Yang

In this paper, we propose a novel DEC model, which we named the deep embedded clustering model with cluster-level representation learning (DECCRL) to jointly learn cluster and instance level representations.

Clustering Contrastive Learning +2

Improved Target-specific Stance Detection on Social Media Platforms by Delving into Conversation Threads

no code implementations6 Nov 2022 Yupeng Li, Haorui He, Shaonan Wang, Francis C. M. Lau, Yunya Song

In response, we address a new task called conversational stance detection which is to infer the stance towards a given target (e. g., COVID-19 vaccination) when given a data instance and its corresponding conversation thread.

Benchmarking Opinion Mining +1

Label-dependent and event-guided interpretable disease risk prediction using EHRs

1 code implementation18 Jan 2022 Shuai Niu, Yunya Song, Qing Yin, Yike Guo, Xian Yang

Thirdly, both label-dependent and event-guided representations are integrated to make a robust prediction, in which the interpretability is enabled by the attention weights over words from medical notes.

Label Dependent Attention Model for Disease Risk Prediction Using Multimodal Electronic Health Records

1 code implementation18 Jan 2022 Shuai Niu, Qing Yin, Yunya Song, Yike Guo, Xian Yang

In this paper, we propose a label dependent attention model LDAM to 1) improve the interpretability by exploiting Clinical-BERT (a biomedical language model pre-trained on a large clinical corpus) to encode biomedically meaningful features and labels jointly; 2) extend the idea of joint embedding to the processing of time-series data, and develop a multi-modal learning framework for integrating heterogeneous information from medical notes and time-series health status indicators.

Language Modelling Time Series +1

A Synthetic Approach for Recommendation: Combining Ratings, Social Relations, and Reviews

no code implementations11 Jan 2016 Guang-Neng Hu, Xin-yu Dai, Yunya Song, Shu-Jian Huang, Jia-Jun Chen

Recommender systems (RSs) provide an effective way of alleviating the information overload problem by selecting personalized choices.

Recommendation Systems

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