Search Results for author: Linhong Zhu

Found 7 papers, 1 papers with code

Deep Reinforcement Learning for Personalized Search Story Recommendation

no code implementations26 Jul 2019 Jason, Zhang, Junming Yin, Dongwon Lee, Linhong Zhu

In recent years, \emph{search story}, a combined display with other organic channels, has become a major source of user traffic on platforms such as e-commerce search platforms, news feed platforms and web and image search platforms.

Image Retrieval Imitation Learning +1

Label Propagation on K-partite Graphs with Heterophily

no code implementations21 Jan 2017 Dingxiong Deng, Fan Bai, Yiqi Tang, Shuigeng Zhou, Cyrus Shahabi, Linhong Zhu

In this paper, for the first time, we study label propagation in heterogeneous graphs under heterophily assumption.

The DARPA Twitter Bot Challenge

no code implementations20 Jan 2016 V. S. Subrahmanian, Amos Azaria, Skylar Durst, Vadim Kagan, Aram Galstyan, Kristina Lerman, Linhong Zhu, Emilio Ferrara, Alessandro Flammini, Filippo Menczer, Andrew Stevens, Alexander Dekhtyar, Shuyang Gao, Tad Hogg, Farshad Kooti, Yan Liu, Onur Varol, Prashant Shiralkar, Vinod Vydiswaran, Qiaozhu Mei, Tim Hwang

A number of organizations ranging from terrorist groups such as ISIS to politicians and nation states reportedly conduct explicit campaigns to influence opinion on social media, posing a risk to democratic processes.

Scalable Link Prediction in Dynamic Networks via Non-Negative Matrix Factorization

no code implementations13 Nov 2014 Linhong Zhu, Dong Guo, Junming Yin, Greg Ver Steeg, Aram Galstyan

We propose a scalable temporal latent space model for link prediction in dynamic social networks, where the goal is to predict links over time based on a sequence of previous graph snapshots.

Link Prediction

Tripartite Graph Clustering for Dynamic Sentiment Analysis on Social Media

no code implementations24 Feb 2014 Linhong Zhu, Aram Galstyan, James Cheng, Kristina Lerman

We further investigate the evolution of user-level sentiments and latent feature vectors in an online framework and devise an efficient online algorithm to sequentially update the clustering of tweets, users and features with newly arrived data.

Graph Clustering Sentiment Analysis

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