Big data implementation in the tourism industry with the integration of Singular Value Decomposition (SVD)

Abstract

Big Data is a critical application of service computing since it enables anticipatory and vital human services. Alternatively, Big Data as a Service can be achieved by efficiently processing large data sets. It has three distinct properties from unstructured, semi-structured, and structured data. Big Data has complicated unified data representation and processing. Moreover, the tourism business generates more unstructured, semi-structured, and structured data. For sustainable tourism innovation and enhancement, this huge collection of diverse data must be examined and translated into a strategic plan. This study attempts to better understand the benefits of Big Data and how it can be used efficiently in the tourism business. Here, post also explores how to utilize SVD to evaluate and optimize heterogeneous data while saving memory. A unified tensor model for SVD incremental analysis of heterogeneous data is proposed. Tensor extension represents data as sub-tensors that are linked. It works well for lowering data dimension and displaying large data sets. The integration collects and analyzes huge volumes of data to find tourism industry trends and provide a data-driven tourism strategy.