KDD

Bio+Clinical BERT, BERT Base, and CNN Performance Comparison for Predicting Drug-Review Satisfaction

Yue Ling

Comments KDD 2023 Workshop on Applied Data Science for Healthcare

Harnessing the Web and Knowledge Graphs for Automated Impact Investing Scoring

Qingzhi Hu, Daniel Daza, Laurens Swinkels, Kristina Ūsaitė, Robbert-Jan 't Hoen, Paul Groth

Comments Presented at the KDD 2023 Workshop - Fragile Earth: AI for Climate Sustainability

Maximizing Neutrality in News Ordering

Rishi Advani, Paolo Papotti, Abolfazl Asudeh

Comments 14 pages, 13 figures, accepted to KDD '23

Journal ref Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '23) (2023) 11--24

kNN-Embed: Locally Smoothed Embedding Mixtures For Multi-interest Candidate Retrieval

Ahmed El-Kishky, Thomas Markovich, Kenny Leung, Frank Portman, Aria Haghighi, Ying Xiao

Comments Pacific-Asia Conference on Knowledge Discovery and Data Mining. Cham: Springer Nature Switzerland, 2023 (PAKDD 2023)

Exploratory Analysis of Covid-19 Tweets using Topic Modeling, UMAP, and DiGraphs

Catherine Ordun, Sanjay Purushotham, Edward Raff

Journal ref Aug. 2020, epiDAMIK 3.0: The 3rd International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Multimodal Indoor Localisation in Parkinson's Disease for Detecting Medication Use: Observational Pilot Study in a Free-Living Setting

Ferdian Jovan, Catherine Morgan, Ryan McConville, Emma L. Tonkin, Ian Craddock, Alan Whone

Comments 11 pages, 4 figures, 4 tables

Journal ref Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023)

Seasonality Based Reranking of E-commerce Autocomplete Using Natural Language Queries

Prateek Verma, Shan Zhong, Xiaoyu Liu, Adithya Rajan

Comments Accepted at The 6th Workshop on e-Commerce and NLP (ECNLP 6), KDD'23, Long Beach, CA

MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction

Jianghao Lin, Yanru Qu, Wei Guo, Xinyi Dai, Ruiming Tang, Yong Yu, Weinan Zhang

Comments KDD 2023

Balancing Approach for Causal Inference at Scale

Sicheng Lin, Meng Xu, Xi Zhang, Shih-Kang Chao, Ying-Kai Huang, Xiaolin Shi

Comments KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Abnormal Trading Detection in the NFT Market

Mingxiao Song, Yunsong Liu, Agam Shah, Sudheer Chava

Comments The Undergraduate Consortium at KDD 2023 (KDD-UC)

Graph Contrastive Learning with Generative Adversarial Network

Cheng Wu, Chaokun Wang, Jingcao Xu, Ziyang Liu, Kai Zheng, Xiaowei Wang, Yang Song, Kun Gai

Comments KDD 2023

ViT2EEG: Leveraging Hybrid Pretrained Vision Transformers for EEG Data

Ruiqi Yang, Eric Modesitt

Comments 8 pages, 6 for article, 1 for citation, 1 for appendix. Accepted to KDD-UC 2023

CARL-G: Clustering-Accelerated Representation Learning on Graphs

William Shiao, Uday Singh Saini, Yozen Liu, Tong Zhao, Neil Shah, Evangelos E. Papalexakis

Comments 14 pages. Accepted at KDD 2023

Metric@CustomerN: Evaluating Metrics at a Customer Level in E-Commerce

Mayank Singh, Emily Ray, Marc Ferradou, Andrea Barraza-Urbina

Comments Accepted to evalRS 2023@KDD

One-shot Joint Extraction, Registration and Segmentation of Neuroimaging Data

Yao Su, Zhentian Qian, Lei Ma, Lifang He, Xiangnan Kong

Comments Published as a research track paper at KDD 2023. Code: https://github.com/Anonymous4545/JERS

HUGE: Huge Unsupervised Graph Embeddings with TPUs

Brandon Mayer, Anton Tsitsulin, Hendrik Fichtenberger, Jonathan Halcrow, Bryan Perozzi

Comments As appeared at KDD 2023

Automatically Evaluating Opinion Prevalence in Opinion Summarization

Christopher Malon

Comments The 6th Workshop on e-Commerce and NLP (KDD 2023)

Beep: Balancing Effectiveness and Efficiency when Finding Multivariate Patterns in Racket Sports

Jiang Wu, Dongyu Liu, Ziyang Guo, Yingcai Wu

Comments This work is accepted in the KDD 2023 Workshop on Data Science and AI for Sports

Unbiased Delayed Feedback Label Correction for Conversion Rate Prediction

Yifan Wang, Peijie Sun, Min Zhang, Qinglin Jia, Jingjie Li, Shaoping Ma

Comments accepted by KDD 2023

EvalRS 2023. Well-Rounded Recommender Systems For Real-World Deployments

Federico Bianchi, Patrick John Chia, Ciro Greco, Claudio Pomo, Gabriel Moreira, Davide Eynard, Fahd Husain, Jacopo Tagliabue

Comments EvalRS 2023 is a workshop at KDD23. Code and hackathon materials: KDD-2023" target="_blank" rel="noopener">https://github.com/RecList/evalRS-KDD-2023

Shift-Robust Molecular Relational Learning with Causal Substructure

Namkyeong Lee, Kanghoon Yoon, Gyoung S. Na, Sein Kim, Chanyoung Park

Comments KDD 2023

Tapestry of Time and Actions: Modeling Human Activity Sequences using Temporal Point Process Flows

Vinayak Gupta, Srikanta Bedathur

Comments Extended version of Gupta and Bedathur [arXiv:2206.05291] (SIGKDD 2022). Under review in a journal

Mitigating Bias in Conversations: A Hate Speech Classifier and Debiaser with Prompts

Shaina Raza, Chen Ding, Deval Pandya

Comments Accepted KDD - Data Science for Social Good

Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay

Thomas M. McDonald, Lucas Maystre, Mounia Lalmas, Daniel Russo, Kamil Ciosek

Comments Presented at the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '23)

LightPath: Lightweight and Scalable Path Representation Learning

Sean Bin Yang, Jilin Hu, Chenjuan Guo, Bin Yang, Christian S. Jensen

Comments This paper has been accepted by ACM SIGKDD-23

Multi-Grained Multimodal Interaction Network for Entity Linking

Pengfei Luo, Tong Xu, Shiwei Wu, Chen Zhu, Linli Xu, Enhong Chen

Comments Accepted by KDD 2023

FedDefender: Client-Side Attack-Tolerant Federated Learning

Sungwon Park, Sungwon Han, Fangzhao Wu, Sundong Kim, Bin Zhu, Xing Xie, Meeyoung Cha

Comments KDD'23 research track accepted

Examining the Effects of Degree Distribution and Homophily in Graph Learning Models

Mustafa Yasir, John Palowitch, Anton Tsitsulin, Long Tran-Thanh, Bryan Perozzi

Comments Accepted to Workshop on Graph Learning Benchmarks at KDD 2023

Joint Latent Topic Discovery and Expectation Modeling for Financial Markets

Lili Wang, Chenghan Huang, Chongyang Gao, Weicheng Ma, Soroush Vosoughi

Comments In Advances in Knowledge Discovery and Data Mining 2023 (PAKDD 2023)

Source-Free Domain Adaptation with Temporal Imputation for Time Series Data

Mohamed Ragab, Emadeldeen Eldele, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Zhenghua Chen

Comments Accepted in KDD'23