activity
20192021
most citedOpenFraming: We brought the ML; you bring the data. Interact with your data and discover its frames

3 citations · 7 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG20211 cited

Tri-Branch Convolutional Neural Networks for Top- Focused Academic Performance Prediction

Chaoran Cui, Jian Zong, Yuling Ma +4

Academic performance prediction aims to leverage student-related information to predict their future academic outcomes, which is beneficial to numerous educational applications, su…

cs.IR2021

DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation

Lei Guo, Li Tang, Tong Chen +3

Shared-account Cross-domain Sequential recommendation (SCSR) is the task of recommending the next item based on a sequence of recorded user behaviors, where multiple users share a…

cs.IR2021

Hierarchical Hyperedge Embedding-based Representation Learning for Group Recommendation

Lei Guo, Hongzhi Yin, Tong Chen +2

In this work, we study group recommendation in a particular scenario, namely Occasional Group Recommendation (OGR). Most existing works have addressed OGR by aggregating group memb…

cs.CL20203 cited

OpenFraming: We brought the ML; you bring the data. Interact with your data and discover its frames

Alyssa Smith, David Assefa Tofu, Mona Jalal +7

When journalists cover a news story, they can cover the story from multiple angles or perspectives. A news article written about COVID-19 for example, might focus on personal preve…

cs.HC20193 cited

BUOCA: Budget-Optimized Crowd Worker Allocation

Mehrnoosh Sameki, Sha Lai, Kate K. Mays +3

Due to concerns about human error in crowdsourcing, it is standard practice to collect labels for the same data point from multiple internet workers. We here show that the resultin…