activity
20172019
most citedTouch Your Heart: A Tone-aware Chatbot for Customer Care on Social Media

39 citations · 60 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CL2019

An Empirical Study of Factors Affecting Language-Independent Models

Xiaotong Liu, Yingbei Tong, Anbang Xu +1

Scaling existing applications and solutions to multiple human languages has traditionally proven to be difficult, mainly due to the language-dependent nature of preprocessing and f…

cs.LG2018★ 12 cited

Characterizing machine learning process: A maturity framework

Rama Akkiraju, Vibha Sinha, Anbang Xu +5

Academic literature on machine learning modeling fails to address how to make machine learning models work for enterprises. For example, existing machine learning processes cannot…

cs.AI2018★ 1 cited

Challenge AI Mind: A Crowd System for Proactive AI Testing

Siwei Fu, Anbang Xu, Xiaotong Liu +2

Artificial Intelligence (AI) has burrowed into our lives in various aspects; however, without appropriate testing, deployed AI systems are often being criticized to fail in critica…

cs.HC2018★ 39 cited

Touch Your Heart: A Tone-aware Chatbot for Customer Care on Social Media

Tianran Hu, Anbang Xu, Zhe Liu +5

Chatbot has become an important solution to rapidly increasing customer care demands on social media in recent years. However, current work on chatbot for customer care ignores a k…

cs.HC2017

Raising Awareness of Conveyed Personality In Social Media Traces

Bin Xu, Liang Gou, Anbang Xu +2

Users' persistent social media contents like posts on Facebook Timeline are presented as an "exhibition" about the person to others, and managing these exhibitional contents for im…

cs.SI2017

25 Tweets to Know You: A New Model to Predict Personality with Social Media

Pierre-Hadrien Arnoux, Anbang Xu, Neil Boyette +3

Predicting personality is essential for social applications supporting human-centered activities, yet prior modeling methods with users written text require too much input data to…

cs.CL2017★ 8 cited

Fostering User Engagement: Rhetorical Devices for Applause Generation Learnt from TED Talks

Zhe Liu, Anbang Xu, Mengdi Zhang +2

One problem that every presenter faces when delivering a public discourse is how to hold the listeners' attentions or to keep them involved. Therefore, many studies in conversation…

cs.SI2017

Computational Models for Attitude and Actions Prediction

Jalal Mahmud, Geli Fei, Anbang Xu +2

In this paper, we present computational models to predict Twitter users' attitude towards a specific brand through their personal and social characteristics. We also predict their…