KDD

Constructing High Precision Knowledge Bases with Subjective and Factual Attributes

Ari Kobren, Pablo Barrio, Oksana Yakhnenko, Johann Hibschman, Ian Langmore

Comments Appears at KDD 2019 Applied Data Science Track, 19 pages

Actions Speak Louder Than Goals: Valuing Player Actions in Soccer

Tom Decroos, Lotte Bransen, Jan Van Haaren, Jesse Davis

Comments Significant update of the paper. The same core idea, but with a clearer methodology, applied on a different data set, and more extensive experiments. 9 pages + 2 pages appendix. To be published at SIGKDD 2019

Predicting assisted ventilation in Amyotrophic Lateral Sclerosis using a mixture of experts and conformal predictors

Telma Pereira, Sofia Pires, Marta Gromicho, Susana Pinto, Mamede de Carvalho, Sara C. Madeira

Journal ref KDD 2019 Workshop on Applied Data Science for Healthcare

Towards Knowledge-Based Personalized Product Description Generation in E-commerce

Qibin Chen, Junyang Lin, Yichang Zhang, Hongxia Yang, Jingren Zhou, Jie Tang

Comments KDD 2019 Camera-ready. Website: https://sites.google.com/view/kobe2019

AiAds: Automated and Intelligent Advertising System for Sponsored Search

Xiao Yang, Daren Sun, Ruiwei Zhu, Tao Deng, Zhi Guo, Jiao Ding, Shouke Qin, Zongyao Ding, Yanfeng Zhu

Comments Accepted at ACM KDD 2019. arXiv admin note: text overlap with arXiv:1701.05946 by other authors

Real-time Event Detection on Social Data Streams

Mateusz Fedoryszak, Brent Frederick, Vijay Rajaram, Changtao Zhong

Comments Accepted as a full paper at KDD 2019 on April 29, 2019

Computational Phenotype Discovery via Probabilistic Independence

Thomas A. Lasko, Diego A. Mesa

Comments Presented at KDD Workshop on Applied Data Science for Healthcare 2019

Optuna: A Next-generation Hyperparameter Optimization Framework

Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, Masanori Koyama

Comments 10 pages, Accepted at KDD 2019 Applied Data Science track

Infant Mortality Prediction using Birth Certificate Data

Antonia Saravanou, Clemens Noelke, Nicholas Huntington, Dolores Acevedo-Garcia, Dimitrios Gunopulos

Comments DSHealth Workshop, Health Day, SIGKDD 2019

Interpretable and Steerable Sequence Learning via Prototypes

Yao Ming, Panpan Xu, Huamin Qu, Liu Ren

Comments Accepted as a full paper at KDD 2019 on May 8, 2019

Journal ref Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019

Snomed2Vec: Random Walk and Poincaré Embeddings of a Clinical Knowledge Base for Healthcare Analytics

Khushbu Agarwal, Tome Eftimov, Raghavendra Addanki, Sutanay Choudhury, Suzanne Tamang, Robert Rallo

Comments 2019 KDD Workshop on Applied Data Science for Healthcare (DSHealth '19). https://gitlab.com/agarwal.khushbu/Snomed2Vec

Click-Through Rate Prediction with the User Memory Network

Wentao Ouyang, Xiuwu Zhang, Shukui Ren, Li Li, Zhaojie Liu, Yanlong Du

Comments Accepted by DLP-KDD 2019 (1st International Workshop on Deep Learning Practice for High-Dimensional Sparse Data; with KDD 2019). arXiv admin note: text overlap with arXiv:1906.04365, arXiv:1906.03776

Empowering A* Search Algorithms with Neural Networks for Personalized Route Recommendation

Jingyuan Wang, Ning Wu, Wayne Xin Zhao, Fanzhang Peng, Xin Lin

Comments 9 pages, 25TH ACM SIGKDD Conference On Knowledge Discovery And Data Mining

An Information Extraction and Knowledge Graph Platform for Accelerating Biochemical Discoveries

Matteo Manica, Christoph Auer, Valery Weber, Federico Zipoli, Michele Dolfi, Peter Staar, Teodoro Laino, Costas Bekas, Akihiro Fujita, Hiroki Toda, Shuichi Hirose, Yasumitsu Orii

Comments 4 pages, 1 figure, Workshop on Applied Data Science for Healthcare at KDD, Anchorage, AK, 2019

Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction

Wentao Ouyang, Xiuwu Zhang, Li Li, Heng Zou, Xin Xing, Zhaojie Liu, Yanlong Du

Comments Accepted by KDD 2019

Detecting Social Influence in Event Cascades by Comparing Discriminative Rankers

Sandeep Soni, Shawn Ling Ramirez, Jacob Eisenstein

Comments Accepted to the SIGKDD Workshop on Causal Discovery, 2019

A Systematic Approach to Detect Hierarchical Healthcare Cost Drivers and Interpretable Change Patterns

Ta-Hsin Li, Huijing Jiang, Kevin Tran, Gigi Yuen-Reed, Bob Kelley, Thomas Halvorson

Comments 2019 KDD DS Healthcare workshop

OCC: A Smart Reply System for Efficient In-App Communications

Yue Weng, Huaixiu Zheng, Franziska Bell, Gokhan Tur

Comments link to demo: https://www.youtube.com/watch?v=nOffUT7rS0A&t=32s

Journal ref KDD 19, August 4-8, 2019, Anchorage, AK, USA

An Adaptive Approach for Anomaly Detector Selection and Fine-Tuning in Time Series

Hui Ye, Xiaopeng Ma, Qingfeng Pan, Huaqiang Fang, Hang Xiang, Tongzhen Shao

Comments 7 pages, 5 figures it has been accepted to DLP-KDD 2019 workshop

Connecting Lyapunov Control Theory to Adversarial Attacks

Arash Rahnama, Andre T. Nguyen, Edward Raff

Comments 8 pages, 3 figures, AdvML'19: Workshop on Adversarial Learning Methods for Machine Learning and Data Mining at KDD

An AI-Augmented Lesion Detection Framework For Liver Metastases With Model Interpretability

Xin J. Hunt, Ralph Abbey, Ricky Tharrington, Joost Huiskens, Nina Wesdorp

Comments 4 pages, 2 figures, 2019 KDD Workshop on Applied Data Science for Healthcare

Learning Latent Events from Network Message Logs

Siddhartha Satpathi, Supratim Deb, R Srikant, He Yan

Comments To Appear in IEEE Transactions on Networking, Appeared in Workshop on MiLeTS, SIGKDD 2018

Leveraging Linguistic Characteristics for Bipolar Disorder Recognition with Gender Differences

Yen-Hao Huang, Yi-Hsin Chen, Fernando Henrique Calderon Alvarado, Ssu-Rui Lee, Shu-I Wu, Yuwen Lai, Yi-Shin Chen

Comments Accepted by DSHealth '19: 2019 KDD Workshop on Applied Data Science for Healthcare

Medical Concept Representation Learning from Claims Data and Application to Health Plan Payment Risk Adjustment

Qiu-Yue Zhong, Andrew H. Fairless, Jasmine M. McCammon, Farbod Rahmanian

Comments Accepted as a poster presentation at the 2019 KDD Workshop on Applied Data Science for Healthcare (KDD-DSHealth2019), Aug 5, 2019, Anchorage, Alaska USA

Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation

Wenjie Shang, Yang Yu, Qingyang Li, Zhiwei Qin, Yiping Meng, Jieping Ye

Comments Appears in KDD 2019

AMAD: Adversarial Multiscale Anomaly Detection on High-Dimensional and Time-Evolving Categorical Data

Zheng Gao, Lin Guo, Chi Ma, Xiao Ma, Kai Sun, Hang Xiang, Xiaoqiang Zhu, Hongsong Li, Xiaozhong Liu

Comments Accepted by 2019 KDD Workshop on Deep Learning Practice for High-Dimensional Sparse Data

Modeling the Uncertainty in Electronic Health Records: a Bayesian Deep Learning Approach

Riyi Qiu, Yugang Jia, Mirsad Hadzikadic, Michael Dulin, Xi Niu, Xin Wang

Comments 4 pages, 3 figures, 2 tables. 2019 KDD Workshop on Applied Data Science for Healthcare. Anchorage, AK, USA, August 5, 2019

Activity2Vec: Learning ADL Embeddings from Sensor Data with a Sequence-to-Sequence Model

Alireza Ghods, Diane J. Cook

Comments 4 pages, 2 figures, DSHealth: 2019 KDD workshop on Applied data science in Healthcare

Infer Implicit Contexts in Real-time Online-to-Offline Recommendation

Xichen Ding, Jie Tang, Tracy Liu, Cheng Xu, Yaping Zhang, Feng Shi, Qixia Jiang, Dan Shen

Comments 9 pages,KDD,KDD2019

Case-Based Reasoning for Assisting Domain Experts in Processing Fraud Alerts of Black-Box Machine Learning Models

Hilde J. P. Weerts, Werner van Ipenburg, Mykola Pechenizkiy

Comments Will be published in proceedings of KDD workshop on Anomaly Detection in Finance 2019