ligature 发表于 2025-3-26 21:08:02
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Big Data for Social Media Analysis During the COVID-19 Pandemic: An Emotion Analysis Based on Influyears, news and social media were covered with information, updates, and daily/regular reports on the COVID-19 pandemic. When face-to-face activities were restricted, people started to use social networks more than before. The situation led to the empowerment of digital media, such as social media a幻想 发表于 2025-3-27 06:26:00
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Optimized Clustering Model for Healthcare Sentiments on Twitter: A Big Data Analysis Approache social events, e-commerce products, healthcare, etc. This chapter proposes a best-fitted clustering method to classify sentiment samples related to healthcare topics. Thus, we examine other clustering models with keyword extraction methods on the real healthcare datasets collected from Twitter. Th壕沟 发表于 2025-3-27 16:56:48
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Saeid Pourroostaei Ardakani,Ali CheshmehzangiCovers big data solutions in urban sustainability applications—mainly smart transportation and healthcare systems.Remains as the only book dealing with data analytic problems in urban sustainability aSinus-Rhythm 发表于 2025-3-28 01:32:31
Urban Sustainabilityhttp://image.papertrans.cn/b/image/185615.jpgcornucopia 发表于 2025-3-28 05:55:17
Introducing Relational Political Analysise current information age. The chapter starts with an overview of Big Data analytics for urban systems and follows the discussions from the sector-based perspectives.It then explores Big Data Applications (BDA) in two key areas of smart transportation and healthcare, particularly in cities and as pa不爱防注射 发表于 2025-3-28 06:24:12
Robert Fantina,Andriy Storozhuk,Kamal Goyaltive impacts of such delays. Machine learning-enabled Big data solutions have been widely utilized in recent studies to anticipate aircraft delays. They need a data pre-processing to understand and grasp the relevance of each data attribute. The results of data attribute relevance are used to filter高兴一回 发表于 2025-3-28 13:50:50
Robert Fantina,Andriy Storozhuk,Kamal Goyalontribute to society’s efficient production and development, particularly in optimising urban systems. This chapter aims to build a precise model to predict the number of freight vehicles in future timestamps based on historical data provided On-Board Unit (OBU) datasets in Belgium’s road networks.