activity
20182021
most citedTowards Question-based Recommender Systems

76 citations · 83 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV20215 cited

Paint4Poem: A Dataset for Artistic Visualization of Classical Chinese Poems

Dan Li, Shuai Wang, Jie Zou +4

In this work we propose a new task: artistic visualization of classical Chinese poems, where the goal is to generatepaintings of a certain artistic style for classical Chinese poem…

cs.AI20212 cited

Category Aware Explainable Conversational Recommendation

Nikolaos Kondylidis, Jie Zou, Evangelos Kanoulas

Most conversational recommendation approaches are either not explainable, or they require external user's knowledge for explaining or their explanations cannot be applied in real t…

cs.IR2020

An Empirical Study of Clarifying Question-Based Systems

Jie Zou, Evangelos Kanoulas, Yiqun Liu

Search and recommender systems that take the initiative to ask clarifying questions to better understand users' information needs are receiving increasing attention from the resear…

cs.IR202076 cited

Towards Question-based Recommender Systems

Jie Zou, Yifan Chen, Evangelos Kanoulas

Conversational and question-based recommender systems have gained increasing attention in recent years, with users enabled to converse with the system and better control recommenda…

cs.IR2019

Learning to Ask: Question-based Sequential Bayesian Product Search

Jie Zou, Evangelos Kanoulas

Product search is generally recognized as the first and foremost stage of online shopping and thus significant for users and retailers of e-commerce. Most of the traditional retrie…

cs.IR2018

Technology Assisted Reviews: Finding the Last Few Relevant Documents by Asking Yes/No Questions to Reviewers

Jie Zou, Dan Li, Evangelos Kanoulas

The goal of a technology-assisted review is to achieve high recall with low human effort. Continuous active learning algorithms have demonstrated good performance in locating the m…