A large-scale chinese short-text conversation dataset

Y Wang, P Ke, Y Zheng, K Huang, Y Jiang… - … Processing and Chinese …, 2020 - Springer
The advancements of neural dialogue generation models show promising results on
modeling short-text conversations. However, training such models usually needs a large …

[PDF][PDF] " Chitty-Chitty-Chat Bot": Deep Learning for Conversational AI.

R Yan - IJCAI, 2018 - ijcai.org
Conversational AI is of growing importance since it enables easy interaction interface
between humans and computers. Due to its promising potential and alluring commercial …

Adsgnn: Behavior-graph augmented relevance modeling in sponsored search

C Li, B Pang, Y Liu, H Sun, Z Liu, X Xie… - Proceedings of the 44th …, 2021 - dl.acm.org
Sponsored search ads appear next to search results when people look for products and
services on search engines. In recent years, they have become one of the most lucrative …

Interview choice reveals your preference on the market: To improve job-resume matching through profiling memories

R Yan, R Le, Y Song, T Zhang, X Zhang… - Proceedings of the 25th …, 2019 - dl.acm.org
Online recruitment services are now rapidly changing the landscape of hiring traditions on
the job market. There are hundreds of millions of registered users with resumes, and tens of …

Coupled context modeling for deep chit-chat: towards conversations between human and computer

R Yan, D Zhao - Proceedings of the 24th ACM SIGKDD international …, 2018 - dl.acm.org
To have automatic conversations between human and computer is regarded as one of the
most hardcore problems in computer science. Conversational systems are of growing …

Joint learning of response ranking and next utterance suggestion in human-computer conversation system

R Yan, D Zhao, WE - Proceedings of the 40th international ACM SIGIR …, 2017 - dl.acm.org
Conversation systems are of growing importance since they enable an easy interaction
interface between humans and computers: using natural languages. To build a conversation …

SSDMV: Semi-supervised deep social spammer detection by multi-view data fusion

C Li, S Wang, L He, SY Philip… - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
The explosive use of social media makes it a popular platform for malicious users, known as
social spammers, to overwhelm legitimate users with unwanted content. Most existing social …

Leveraging bidding graphs for advertiser-aware relevance modeling in sponsored search

S Bi, C Li, X Han, Z Liu, X Xie, H Huang… - Findings of the …, 2021 - aclanthology.org
Recently, sponsored search has become one of the most lucrative channels for marketing.
As the fundamental basis of sponsored search, relevance modeling has attracted increasing …

Unsupervised technique for training an engagement classifier in chat-based group conversation

DA Conley, L Krishnamurthy, S Sudarsan… - US Patent …, 2021 - Google Patents
An engagement classifier for a group chatbot is trained by leveraging the implicit dataset
generated by humans engag ing in both direct messages as well as group conversations …

Why Do Neural Response Generation Models Prefer Universal Replies?

B Wu, N Jiang, Z Gao, M Li, Z Wang, S Li… - arXiv preprint arXiv …, 2018 - arxiv.org
Recent advances in sequence-to-sequence learning reveal a purely data-driven approach
to the response generation task. Despite its diverse applications, existing neural models are …