Large-Scale Disk Failure Prediction [electronic resource] : PAKDD 2020 Competition and Workshop, AI Ops 2020, February 7 – May 15, 2020, Revised Selected Papers /

An Introduction to PAKDD CUP 2020 Dataset -- PAKDD 2020 Alibaba AIOps Competition-Large-scale Disk Failure Prediction: Third Place Team -- A Voting-based Robust Model for Disk Failure Prediction -- First place solution of PAKDD Cup 2020 -- Anomaly Detection of Hard Disk Drives based on Multi-scale Feature -- Disk Failure Prediction: an in-depth comparison between deep neural networks and tree-based models -- PAKDD2020 Alibaba AI Ops Competition: Large-Scale Disk Failure Prediction -- SHARP: SMART HDD Anomaly Risk Prediction -- Tree-based model with advanced data preprocessing for large scale hard disk failure prediction -- PAKDD2020 Alibaba AI Ops Competition: An SPE-LightGBM Approach -- Noise Feature Selection Method in PAKDD 2020 Alibaba AI Ops Competition: Large-Scale Disk Failure Prediction -- Characterizing and Modeling for Proactive Disk Failure Prediction to Improve Reliability of Data Centers -- Summary of PAKDD CUP 2020: From Organizers’ Perspective.

This book constitutes the thoroughly refereed post-competition proceedings of the AI Ops Competition on Large-Scale Disk Failure Prediction, conducted between February 7th and May 15, 2020 on the Alibaba Cloud Tianchi Platform. A dedicated workshop, featuring the best performing teams of the competition, was held at the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, in Singapore, in April 2019. Due to the COVID-19 pandemic, the workshop was hosted online. This book includes 13 selected contributions: an introduction to dataset, selected approaches of the competing teams and the competition summary, describing the competition task, practical challenges, evaluation metrics, etc.