activity
20202022
most citedStudying Product Competition Using Representation Learning

6 citations · 16 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL20225 cited

On Analyzing the Role of Image for Visual-enhanced Relation Extraction

Lei Li, Xiang Chen, Shuofei Qiao +3

Multimodal relation extraction is an essential task for knowledge graph construction. In this paper, we take an in-depth empirical analysis that indicates the inaccurate informatio…

cs.CL20225 cited

Bridging the Gap between Reality and Ideality of Entity Matching: A Revisiting and Benchmark Re-Construction

Tianshu Wang, Hongyu Lin, Cheng Fu +6

Entity matching (EM) is the most critical step for entity resolution (ER). While current deep learningbased methods achieve very impressive performance on standard EM benchmarks, t…

cs.LG2022

NeuralKG: An Open Source Library for Diverse Representation Learning of Knowledge Graphs

Wen Zhang, Xiangnan Chen, Zhen Yao +10

NeuralKG is an open-source Python-based library for diverse representation learning of knowledge graphs. It implements three different series of Knowledge Graph Embedding (KGE) met…

cs.LG2021

Interpretable performance analysis towards offline reinforcement learning: A dataset perspective

Chenyang Xi, Bo Tang, Jiajun Shen +3

Offline reinforcement learning (RL) has increasingly become the focus of the artificial intelligent research due to its wide real-world applications where the collection of data ma…

cs.LG20206 cited

Studying Product Competition Using Representation Learning

Fanglin Chen, Xiao Liu, Davide Proserpio +2

Studying competition and market structure at the product level instead of brand level can provide firms with insights on cannibalization and product line optimization. However, it…