Advances in recent techniques for scientific data collection in the era of big data allow for the
systematic accumulation of large quantities of data at various data-capturing sites. Similarly …

Densification of network base stations is indispensable to achieve the stringent Quality of
Service (QoS) requirements of future mobile networks. However, with a dense deployment of …

The generation of collective preference assessments occupies a critical position in deriving
accurate and reliable alternative rankings in the context of large-scale group decision …

In this paper, we study what are the most important factors that deteriorate the performance
of the k-means algorithm, and how much this deterioration can be overcome either by using …

Hospital length of stay of patients is a crucial factor for the effective planning and
management of hospital resources. There is considerable interest in predicting the LoS of …

The amount of text that is generated every day is increasing dramatically. This tremendous
volume of mostly unstructured text cannot be simply processed and perceived by computers …

Symbols are powerful in branding and marketing to represent tourist attractions. By bridging
semiotics, marketing, and data science in the tourism context, this study uncovers the …

Despite progress in perceptual tasks such as image classification, computers still perform
poorly on cognitive tasks such as image description and question answering. Cognition is …

Data clustering is a commonly used data processing technique in many fields, which divides
objects into different clusters in terms of some similarity measure between data points …

Data analysis is used as a common method in modern science research, which is across
communication science, computer science and biology science. Clustering, as the basic …