activity
20172020
most citedNeural Attentive Session-based Recommendation

30 citations · 45 across the 2 of their papers we have counts for

collaborators

7 papers

cs.CL202015 cited

A Neural Topical Expansion Framework for Unstructured Persona-oriented Dialogue Generation

Minghong Xu, Piji Li, Haoran Yang +4

Unstructured Persona-oriented Dialogue Systems (UPDS) has been demonstrated effective in generating persona consistent responses by utilizing predefined natural language user perso…

cs.IR2019

Improving Outfit Recommendation with Co-supervision of Fashion Generation

Yujie Lin, Pengjie Ren, Zhumin Chen +3

The task of fashion recommendation includes two main challenges: visual understanding and visual matching. Visual understanding aims to extract effective visual features. Visual ma…

cs.CL2019

Thinking Globally, Acting Locally: Distantly Supervised Global-to-Local Knowledge Selection for Background Based Conversation

Pengjie Ren, Zhumin Chen, Christof Monz +2

Background Based Conversations (BBCs) have been introduced to help conversational systems avoid generating overly generic responses. In a BBC, the conversation is grounded in a kno…

cs.CL2019

RefNet: A Reference-aware Network for Background Based Conversation

Chuan Meng, Pengjie Ren, Zhumin Chen +3

Existing conversational systems tend to generate generic responses. Recently, Background Based Conversations (BBCs) have been introduced to address this issue. Here, the generated…

cs.IR2018

RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-based Recommendation

Pengjie Ren, Zhumin Chen, Jing Li +3

Recurrent neural networks for session-based recommendation have attracted a lot of attention recently because of their promising performance. repeat consumption is a common phenome…

cs.IR2018

Attentive Long Short-Term Preference Modeling for Personalized Product Search

Yangyang Guo, Zhiyong Cheng, Liqiang Nie +3

E-commerce users may expect different products even for the same query, due to their diverse personal preferences. It is well-known that there are two types of preferences: long-te…