activity
20162020
most citedCollective Semi-Supervised Learning for User Profiling in Social Media

4 citations · 9 across the 4 of their papers we have counts for

collaborators

6 papers

cs.SI20201 cited

On Predicting Personal Values of Social Media Users using Community-Specific Language Features and Personal Value Correlation

Amila Silva, Pei-Chi Lo, Ee-Peng Lim

Personal values have significant influence on individuals' behaviors, preferences, and decision making. It is therefore not a surprise that personal values of a person could influe…

cs.CV20201 cited

Face to Purchase: Predicting Consumer Choices with Structured Facial and Behavioral Traits Embedding

Zhe Liu, Xianzhi Wang, Lina Yao +3

Predicting consumers' purchasing behaviors is critical for targeted advertisement and sales promotion in e-commerce. Human faces are an invaluable source of information for gaining…

cs.LG2020

JPLink: On Linking Jobs to Vocational Interest Types

Amila Silva, Pei-Chi Lo, Ee-Peng Lim

Linking job seekers with relevant jobs requires matching based on not only skills, but also personality types. Although the Holland Code also known as RIASEC has frequently been us…

cs.LG2019

A Near-Optimal Change-Detection Based Algorithm for Piecewise-Stationary Combinatorial Semi-Bandits

Huozhi Zhou, Lingda Wang, Lav R. Varshney +1

We investigate the piecewise-stationary combinatorial semi-bandit problem. Compared to the original combinatorial semi-bandit problem, our setting assumes the reward distributions…

cs.SI20173 cited

Friendship Maintenance and Prediction in Multiple Social Networks

Roy Ka-Wei Lee, Ee-Peng Lim

Due to the proliferation of online social networks (OSNs), users find themselves participating in multiple OSNs. These users leave their activity traces as they maintain friendship…

cs.SI20164 cited

Collective Semi-Supervised Learning for User Profiling in Social Media

Richard J. Oentaryo, Ee-Peng Lim, Freddy Chong Tat Chua +2

The abundance of user-generated data in social media has incentivized the development of methods to infer the latent attributes of users, which are crucially useful for personaliza…