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Tourism recommendation system: a survey and future research directions

  • 1209: Recent Advances on Social Media Analytics and Multimedia Systems: Issues and Challenges
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Abstract

A Recommendation System (RS) is an intelligent computer based system which provide valuable suggestions to the user and are used in several domains. Social media platforms are the most common internet applications due to the large number of users. The numerous posts, likes, etc. have accrued on social media platforms and can be used in variety of recommendation systems. In this work, the primary focus is the tourism domain, where RS serves as a valuable tool for the tourist to plan his trip. Traditional RS systems only cater to the needs of the tourist by examining few factors. However, there are a large range of factors such as environment factors , actual geo-coordinates, trip destination, preferences of the user etc. that need to be taken into account in order to make a foolproof recommendation to the tourists. Tourism Recommendation Systems (TRS) provide suggestions to the tourists to identify the most suited transport (flight, train, etc.), accommodations, museums, special interest places and other items which are required for the trip. Several techniques are used and a thorough study of various techniques of traditional RS and TRS techniques have been done which are specially designed for tourism domain. Various Artificial Intelligence (AI) techniques have been highlighted which are used to solve the tourist recommendation problem. Also, future research direction has been suggested which would improvise the Quality of Service (QoS) of the RS in tourism industry.

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Authors and Affiliations

  1. Tripura University, Tripura, India

    Joy Lal Sarkar & Abhishek Majumder

  2. Rama Devi Women’s University, Bhubaneswar, India

    Chhabi Rani Panigrahi & Bibudhendu Pati

  3. Assam University, Silchar, India

    Sudipta Roy

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  1. Joy Lal Sarkar
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Sarkar, J.L., Majumder, A., Panigrahi, C.R. et al. Tourism recommendation system: a survey and future research directions. Multimed Tools Appl 82, 8983–9027 (2023). https://doi.org/10.1007/s11042-022-12167-w

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