04846nam 2201225z- 450 991057687810332120220621(CKB)5720000000008394(oapen)https://directory.doabooks.org/handle/20.500.12854/84521(oapen)doab84521(EXLCZ)99572000000000839420202206d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierData Science and Knowledge DiscoveryBaselMDPI - Multidisciplinary Digital Publishing Institute20221 online resource (254 p.)3-0365-4316-3 3-0365-4315-5 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 using scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data to support the decision process. After collecting the data, it is crucial to discover the knowledge. In this step, Knowledge Discovery (KD) tasks are used to create knowledge from structured and unstructured sources (e.g., text, data, and images). The output needs to be in a readable and interpretable format. It must represent knowledge in a manner that facilitates inferencing. KD is applied in several areas, such as education, health, accounting, energy, and public administration. This book includes fourteen excellent articles which discuss this trending topic and present innovative solutions to show the importance of Data Science and Knowledge Discovery to researchers, managers, industry, society, and other communities. The chapters address several topics like Data mining, Deep Learning, Data Visualization and Analytics, Semantic data, Geospatial and Spatio-Temporal Data, Data Augmentation and Text Mining.Computer sciencebicsscInformation technology industriesbicsscactivity recognitionadaptation processArcGISartificial intelligenceattributionauthorshipautomationbig dataBig Databox-counting frameworkchatbotsclassificationcontent base image retrievalCOVID-19crisis reportingcustomer relationship management (CRM)dashboarddata analysisdata analyticsdata augmentationdata miningdata sciencedatabasesdecision systemsdeep featuresdeep learningdigital humanitiesdigital infrastructuresdistracted drivingdriving behaviordriving operation areae-commerceeconomic determinants of open dataESP32 microcontrollerfeature extractionforensic intelligencefractal dimensiongeoinformation technologygovernance and social institutionshumanitiesICTinformation systemsinterdisciplinary researchinternet of thingsioCOVID19journalistslinked open dataLoRaWANmachine learningmedia analyticsmedia criticismmultimedia document retrievaln/aneural networksnews mediaopen government dataprediction by partial matchingpublic healthrough setsrule based systemsSARS-CoV-2script Pythonsemantic information retrievalsmart homessocial sciencesspatio-temporalterritorial road networktext miningtextbook researchThe Things NetworkWeb IntelligenceWebGISComputer scienceInformation technology industriesPortela Filipeedt1268012Portela FilipeothBOOK9910576878103321Data Science and Knowledge Discovery3021749UNINA