Recommender System with Machine Learning and Artificial Intelligence

32Es of TIS: A Review of Information Exchange and Extraction in Tourism Information Systems

Malik M. Saad Missen¹*, Mickaël Coustaty², Hina Asmat¹, Amnah Firdous³, Nadeem Akhtar¹, Muhammad Akram⁴ and V. B. Surya Prasath⁵

¹ Department of Computer Science and Information Technology, The Islamia University of Bahawalpur, Pakistan

² Laboratoire Informatique, Image et Interaction (L3i), Facultès des Sciences et Technologies, University of La Rochelle, France

³ Department of Computer Science, COMSATS University, Islamabad, Pakistan

⁴ Virtual University of Pakistan, Lahore, Pakistan

⁵ Department of Electrical Engineering and Computer Science, University of Cincinnati, Ohio, United States

Abstract

Tourism industry could be one of the largest sources of revenue for any country. After the emergence of Web 2.0, it is also one of the largest data intensive industries in the world. Tourism-rich countries often use Tourism Information Systems (TIS) for management of tourism-related data. These systems are used are used on several levels of tourism stakeholder’s hierarchy from data generation and exchange to intelligent decision making. Data exchange and extraction are core tasks that a generic TIS is supposed to perform. In this chapter, we discuss both of these processes with respect to TIS. We describe the importance of these processes and review how these are being dealt by researchers currently. Further, we highlight the limitations of current approaches of data exchange and extraction ...