Data Science and Knowledge Discovery

• Другие авторы: Portela, Filipe (Редактор)
• Формат: Электронный ресурс Глава книги
• Язык: английский
• Опубликовано: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Предметы: Information technology industries; Computer science; crisis reporting; chatbots; journalists; news media; COVID-19; textbook research; digital humanities; digital infrastructures; data analysis; content base image retrieval; semantic information retrieval; deep features; multimedia document retrieval; data science; open government data; governance and social institutions; economic determinants of open data; geoinformation technology; fractal dimension; territorial road network; box-counting framework; script Python; ArcGIS; internet of things; LoRaWAN; ICT; The Things Network; ESP32 microcontroller; decision systems; rule based systems; databases; rough sets; prediction by partial matching; spatio-temporal; activity recognition; smart homes; artificial intelligence; automation; e-commerce; machine learning; big data; customer relationship management (CRM); distracted driving; driving behavior; driving operation area; data augmentation; feature extraction; authorship; text mining; attribution; neural networks; deep learning; forensic intelligence; dashboard; WebGIS; data analytics; SARS-CoV-2; Big Data; Web Intelligence; media analytics; social sciences; humanities; linked open data; adaptation process; interdisciplinary research; media criticism; classification; information systems; public health; data mining; ioCOVID19; n/a
• Online-ссылка: DOAB: download the publication; DOAB: description of the publication

Data Science (DS) is gaining significant importance in the decision process due to a mix of various areas, including Computer Science, Machine Learning, Math and Statistics, domain/business knowledge, software development, and traditional research. In the business field, DS's application allows...