3: Design of the Proposed System

This chapter discusses about the design adapted in predicting tourist preferences based on hotel ratings using big data analytics.

Nowadays, tourists have depended on the social networking site use to acquire the most essential travel data. With a fast growth in internet, travellers generally share their reviews on social media sites by explaining about the services provided during the journey in respective places. These reviews create huge number of data each passing day and comprise vast number of data sets to create big data for tourist places. However, the content of social media namely the posts, comments, tweets and ratings have supported the big data creation from platform providers. The growth of big data from social media in tourism industry has brought a new excitement wave into the big data analytics field. The data which are shared by tourists on social media sites or travel websites about their experience in travel lead to huge number of reviews which becomes the major source for respective tourists. The tourists can provide positive rating or they can also comment it negatively which could help tourism firms to manage with problems and queries and enable them to work the negative things better so as to acquire the advantages and win new customers better provision of service. Thus, big data is very useful which reduces the time required for browsing of tourists and assist the growth of tourism easily. This solution could review the ratings of tourist travellers, extract the reviews from all this information, offers an overall perspective which would save huge amount of time and ease the decision process for travellers. Fig. 3.1 shows the proposed flow diagram of tourist preferences based on hotel ratings using big data analytics.