Data Science and Machine Learning to Support Business Decisions

A Hybrid AI Framework to Address the Issue of Frequent Missing Values with Application in EHR Systems: the Case of Parkinson’s Disease

Mostafa Amini, California State University Long Beach
Ali Bagheri, Oklahoma State University
Saeed Piri, University of Oregon
Dursun Delen, Oklahoma State University

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Evaluating the Risk of Re-Identification in Data Release Strategies: An Attacker-Centric Approach

Patrick Mesana, HEC Montreal
Pascal Jutras, Purdue University
Julien Crowe, National Bank of Canada
Gregory Vial, HEC Montréal
Gilles Caporossi, HEC Montreal

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Improving the Accuracy of Sequential Recommendation Using a Time-aware Architecture

Ruoxi Sun, University of Wollongong
Jun Yan, University of Wollongong
Fenghui Ren, University of Wollongong
Cong Cao, Zhejiang University of Technology

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Informed Decision-Making through Advancements in Open Set Recognition and Unknown Sample Detection

Atefeh Mahdavi, Florida Institute of Technology
Marco Carvalho, Florida Institute of Technology

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Introduction to the Minitrack on Data Science and Machine Learning to Support Business Decisions

Dursun Delen, Oklahoma State University
Behrooz Davazdahemami, University of Wisconsin-Whitewater
Hamed Zolbanin, University of Dayton

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Reinforcement Learning-based Livestreaming E-commerce Recommendation System

Yi-Ling Lin, National Chengchi University
Shun-Wen Hsiao, National Chengchi University
Szu-Chi Tang, SAS Institute Inc.

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Research on the causes of earthwork foundation pit collapse based on Fault tree and Bayesian network

Donghui Shi, Anhui Jianzhu University
Shuling Gan, Anhui Jianzhu University
Jozef Zurada, University of Louisville
Wang Feilong, AHJZU
Yuanyuan Wang, Anhui Jianzhu University
Jian Guan, University of Louisville

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Robust Optimization for Inference on Machine Learning Generated Variables

Aaron Schecter, University of Georgia
Weifeng Li, University of Georgia

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Sentiment in Big Tech’s Investor Relations: Does the Discourse Predict Future Stock Movements?

David Goldberg, San Diego State University
Sukhwa Hong, University of Hawaii
Eduardo Villacis Calderon, University of Texas - El Paso

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The Positive Impact of Metric Learning on Open Set Nearest Neighbor Classification

Alexander Grote, Karlsruher Institute of Technology
Wolfgang Badewitz, FZI Forschungszentrum Informatik
Michael Thomas Knierim, Karlsruhe Institute of Technology
Christof Weinhardt, Karlsruhe Institute of Technology

Hilton Hawaiian Village, Honolulu, Hawaii

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