activity
20182022
most citedExplainable Fashion Recommendation: A Semantic Attribute Region Guided Approach

14 citations · 21 across the 6 of their papers we have counts for

collaborators

5 papers

cs.LG20211 cited

Estimating Fund-Raising Performance for Start-up Projects from a Market Graph Perspective

Likang Wu, Zhi Li, Hongke Zhao +2

In the online innovation market, the fund-raising performance of the start-up project is a concerning issue for creators, investors and platforms. Unfortunately, existing studies a…

cs.IR20204 cited

Learning the Compositional Visual Coherence for Complementary Recommendations

Zhi Li, Bo Wu, Qi Liu +3

Complementary recommendations, which aim at providing users product suggestions that are supplementary and compatible with their obtained items, have become a hot topic in both aca…

cs.LG2019

Estimating Early Fundraising Performance of Innovations via Graph-based Market Environment Model

Likang Wu, Zhi Li, Hongke Zhao +3

Well begun is half done. In the crowdfunding market, the early fundraising performance of the project is a concerned issue for both creators and platforms. However, estimating the…

cs.IR201914 cited

Explainable Fashion Recommendation: A Semantic Attribute Region Guided Approach

Min Hou, Le Wu, Enhong Chen +3

In fashion recommender systems, each product usually consists of multiple semantic attributes (e.g., sleeves, collar, etc). When making cloth decisions, people usually show prefere…

cs.IR2018

Learning from History and Present: Next-item Recommendation via Discriminatively Exploiting User Behaviors

Zhi Li, Hongke Zhao, Qi Liu +3

In the modern e-commerce, the behaviors of customers contain rich information, e.g., consumption habits, the dynamics of preferences. Recently, session-based recommendations are be…