Title: Behaviour-based analysis of tourism demand in Egypt

Authors: Taheya H. Ahmed; Mervat Abu-Elkheir; Ahmed Abou Elfetouh Saleh

Addresses: Information System Department, Faculty of Computer and Information Sciences, Mansoura University, Egypt ' Information System Department, Faculty of Computer and Information Sciences, Mansoura University, Egypt ' Information System Department, Faculty of Computer and Information Sciences, Mansoura University, Egypt

Abstract: Tourism demand is the total number of persons who travel, or wish to travel, to use tourists' facilities and services at places away from their places of work or residence. Analysis of tourism demand helps companies understand tourists' needs and improves their marketing strategies. Current research for predicting tourism demand is targeted at foreign countries, and the little research targeted at predicting tourism demand in Egypt is based on macro forecasting and not on understanding the collective behaviour of tourists. In this paper, we devise different granularities from tourist data that we collect and use these different granularities to provide different levels of demand prediction. We develop a hybrid prediction framework to analyse tourists' behaviour and infer behaviour rules. These rules will act as recommendations that help to understand tourists' behaviour and their needs, and define future policies regarding tourism in Egypt.

Keywords: tourist demand; clustering; data mining; cobweb; classification; Egyptian tourism.

DOI: 10.1504/IJBIDM.2018.094980

International Journal of Business Intelligence and Data Mining, 2018 Vol.13 No.4, pp.425 - 440

Available online: 17 Jan 2018 *

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