The Recent Advances in Transdisciplinary Data Science〈1st ed. 2022〉 : First Southwest Data Science Conference, SDSC 2022, Waco, TX, USA, March 25–26, 2022, Revised Selected Papers

著者名：Han, Henry (EDT)/Baker, Erich (EDT)

Springer（2023/01/28発売）

• 言語：ENG
• ISBN：9783031233869
• eISBN：9783031233876

Description

This book constitutes the refereed proceedings of the First Southwest Data Science Conference, on The Recent Advances in Transdisciplinary Data Science, SDSC 2022, held in Waco, TX, USA, during March 25–26, 2022.

The 14 full papers and 2 short papers included in this book were carefully reviewed and selected from 72 submissions. They were organized in topical sections as follows: Business and social data science; Health and biological data science; Applied data science, artificial intelligence, and data engineering.

Table of Contents

Business and social data science.-  Forecasting stock excess returns with SEC 8-K filings.- A Fast Initial Response Approach to Sequential Financial Surveillance.- Evaluation of High-value patents in the reverse innovation: a theory and case study from China.- Research on the influence of different fairness reference points on the supply chain enterprises.- Health and biological data science.- EGRE: calculating enrichment between genomic regions.- THSLRR: a low-rank subspace clustering method based on tired random walk similarity and hypergraph regularization constraints.- Traceability analysis of Feng-Flavour Daqu in China.- Visualization of Functional Assignment of Disease Genes and Mutations.- Applied data science, artificial intelligence and data engineering.- Characterizing In-situ Solar Wind Observations Using Clustering Methods.- An improved capsule network for speech emotion recognition.- Distributed Query Processing and Reasoning Over Linked Big Data.- Normal equilibrium fluctuations from chaotic trajectories: Coupled logistic maps.- Matching Code Patterns Across Programming Languages.- Partitionable Programs using Tyro V2.- Analyzing Technical Debt by Mapping Production Logs with Source Code.- EB-FedAvg: Personalized and training efficient Federated Learning with Early-Bird Tickets