activity
20172024
most citedRelation-Aware Neighborhood Matching Model for Entity Alignment

3 citations · 9 across the 6 of their papers we have counts for

collaborators

6 papers

stat.ML2024

Multi-Normal Prototypes Learning for Weakly Supervised Anomaly Detection

Zhijin Dong, Hongzhi Liu, Boyuan Ren +2

Anomaly detection is a crucial task in various domains. Most of the existing methods assume the normal sample data clusters around a single central prototype while the real data ma…

cs.AI2024★ 2 cited

Large Language Model with Graph Convolution for Recommendation

Yingpeng Du, Ziyan Wang, Zhu Sun +6

In recent years, efforts have been made to use text information for better user profiling and item characterization in recommendations. However, text information can sometimes be o…

cs.IR2023★ 2 cited

Bridging the Information Gap Between Domain-Specific Model and General LLM for Personalized Recommendation

Wenxuan Zhang, Hongzhi Liu, Yingpeng Du +4

Generative large language models(LLMs) are proficient in solving general problems but often struggle to handle domain-specific tasks. This is because most of domain-specific tasks,…

cs.IR2023★ 1 cited

Enhancing Job Recommendation through LLM-based Generative Adversarial Networks

Yingpeng Du, Di Luo, Rui Yan +4

Recommending suitable jobs to users is a critical task in online recruitment platforms, as it can enhance users' satisfaction and the platforms' profitability. While existing job r…

cs.AI2020★ 3 cited

Relation-Aware Neighborhood Matching Model for Entity Alignment

Yao Zhu, Hongzhi Liu, Zhonghai Wu +1

Entity alignment which aims at linking entities with the same meaning from different knowledge graphs (KGs) is a vital step for knowledge fusion. Existing research focused on learn…

cs.CR2017★ 1 cited

Android Multi-Level System Permission Management Approach

Yang Luo, Qixun Zhang, Qingni Shen +2

With the expansion of the market share occupied by the Android platform, security issues (especially application security) have become attention focus of researchers. In fact, the…