32 citations · 63 across the 5 of their papers we have counts for
5 papers
Are Interpretations Fairly Evaluated? A Definition Driven Pipeline for Post-Hoc Interpretability
Ninghao Liu, Yunsong Meng, Xia Hu +2
Recent years have witnessed an increasing number of interpretation methods being developed for improving transparency of NLP models. Meanwhile, researchers also try to answer the q…
Explainable Recommender Systems via Resolving Learning Representations
Ninghao Liu, Yong Ge, Li Li +3
Recommender systems play a fundamental role in web applications in filtering massive information and matching user interests. While many efforts have been devoted to developing mor…
Learning to Hash with Graph Neural Networks for Recommender Systems
Qiaoyu Tan, Ninghao Liu, Xing Zhao +3
Graph representation learning has attracted much attention in supporting high quality candidate search at scale. Despite its effectiveness in learning embedding vectors for objects…
Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding
Ninghao Liu, Qiaoyu Tan, Yuening Li +3
Networks have been widely used as the data structure for abstracting real-world systems as well as organizing the relations among entities. Network embedding models are powerful to…
Deep Representation Learning for Social Network Analysis
Qiaoyu Tan, Ninghao Liu, Xia Hu
Social network analysis is an important problem in data mining. A fundamental step for analyzing social networks is to encode network data into low-dimensional representations, i.e…