activity
20162025
most citedAceKG: A Large-scale Knowledge Graph for Academic Data Mining

13 citations · 36 across the 13 of their papers we have counts for

collaborators

13 papers

cs.IR2025

Towards Large-scale Generative Ranking

Yanhua Huang, Yuqi Chen, Xiong Cao +17

Generative recommendation has recently emerged as a promising paradigm in information retrieval. However, generative ranking systems are still understudied, particularly with respe…

cs.SD2022★ 1 cited

Melody Infilling with User-Provided Structural Context

Chih-Pin Tan, Alvin W. Y. Su, Yi-Hsuan Yang

This paper proposes a novel Transformer-based model for music score infilling, to generate a music passage that fills in the gap between given past and future contexts. While exist…

cs.HC2022★ 2 cited

DeepShovel: An Online Collaborative Platform for Data Extraction in Geoscience Literature with AI Assistance

Shao Zhang, Yuting Jia, Hui Xu +3

Geoscientists, as well as researchers in many fields, need to read a huge amount of literature to locate, extract, and aggregate relevant results and data to enable future research…

cs.SI2021★ 2 cited

Overlapping Community Detection in Temporal Text Networks

Shuhan Yan, Yuting Jia, Xinbing Wang

Analyzing the groups in the network based on same attributes, functions or connections between nodes is a way to understand network information. The task of discovering a series of…

cs.AI2020★ 2 cited

High-Order Relation Construction and Mining for Graph Matching

Hui Xu, Liyao Xiang, Youmin Le +4

Graph matching pairs corresponding nodes across two or more graphs. The problem is difficult as it is hard to capture the structural similarity across graphs, especially on large g…

cs.SI2020

Author Name Disambiguation on Heterogeneous Information Network with Adversarial Representation Learning

Haiwen Wang, Ruijie Wang, Chuan Wen +4

Author name ambiguity causes inadequacy and inconvenience in academic information retrieval, which raises the necessity of author name disambiguation (AND). Existing AND methods ca…

cs.LG2019★ 5 cited

On Geometric Structure of Activation Spaces in Neural Networks

Yuting Jia, Haiwen Wang, Shuo Shao +3

In this paper, we investigate the geometric structure of activation spaces of fully connected layers in neural networks and then show applications of this study. We propose an effi…

cs.AI2019★ 6 cited

CommunityGAN: Community Detection with Generative Adversarial Nets

Yuting Jia, Qinqin Zhang, Weinan Zhang +1

Community detection refers to the task of discovering groups of vertices sharing similar properties or functions so as to understand the network data. With the recent development o…

cs.LG2018★ 1 cited

Predictive Modeling with Delayed Information: a Case Study in E-commerce Transaction Fraud Control

Junxuan Li, Yung-wen Liu, Yuting Jia +2

In Business Intelligence, accurate predictive modeling is the key for providing adaptive decisions. We studied predictive modeling problems in this research which was motivated by…

stat.AP2018★ 3 cited

Adaptive Fraud Detection System Using Dynamic Risk Features

Huiying Mao, Yung-wen Liu, Yuting Jia +1

eCommerce transaction frauds keep changing rapidly. This is the major issue that prevents eCommerce merchants having a robust machine learning model for fraudulent transactions det…

cs.AI2018★ 1 cited

Discriminative Data-driven Self-adaptive Fraud Control Decision System with Incomplete Information

Junxuan Li, Yung-wen Liu, Yuting Jia +1

While E-commerce has been growing explosively and online shopping has become popular and even dominant in the present era, online transaction fraud control has drawn considerable a…

cs.IR2018★ 13 cited

AceKG: A Large-scale Knowledge Graph for Academic Data Mining

Ruijie Wang, Yuchen Yan, Jialu Wang +4

Most existing knowledge graphs (KGs) in academic domains suffer from problems of insufficient multi-relational information, name ambiguity and improper data format for large-scale…

cs.SI2016

Text Network Exploration via Heterogeneous Web of Topics

Junxian He, Ying Huang, Changfeng Liu +3

A text network refers to a data type that each vertex is associated with a text document and the relationship between documents is represented by edges. The proliferation of text n…