A PREFERENCE LIST BASED RECOMMENDER SYSTEM FOR TOURISM INDUSTRY, DESIGN AND IMPLEMENTATION Aliakbar Nik Nafs a Computer Engineering Dept., Shahid Bahonar University,Kerman, Iran Arash Nik Nafs b Information Technology Dept., Tarbiat Modarres University, Jalale- Al-Ahmad St., Tehran,Iran M. Masoud Javidi c Computer Science Dept., Shahid Bahonar University,22 Bahman Blvd.,Kerman,Iran ABSTRACT The increasing number of works and studies in the field of e-commerce indicates that e-commerce has become one of the most important concerns of businesses and also researchers. In B2C arena tourism is a leading business worldwide. Tourism exists as a powerful economic force in the development of both community-based and global markets. This Paper concerns on tour recommender systems that are very important in tourism industry. The algorithm used in this approach works on the basis of specifying the preference lists of users and their needs and interests. A procedure for tour itinerary planning is suggested and then sample runs of the implemented program will be discussed. The proposed recommender system in this paper can be viewed as collaborative filtering that incorporates feature, such as age range, budget, interests, and duration of trip and special needs and preferences. KEYWORD Recommender System, Tourism, Collaborative Filtering. 1. INTRODUCTION During recent years e-commerce has been one of the most important goals of researchers as well as programmers. By any account, e-commerce is a big business as well as a profitable one. E-commerce has three main business models: B2C, business-to-business (B2B), and consumer-to- consumer (C2C). B2C, in which online vendors sell products directly to consumers, is the most common (Lin and Wang, 2008). Tourism is the leading application in the B2C (business- to-consumer) arena (Staab and Werthner, 2002). The tourism industry is one of the fastest growing at the global scale. Tourism represents an indispensable source of financial resources for the preservation and restoration of the heritage that otherwise faces shrinking budgets and state transfers and it also generates jobs and income (Russo and Borg, 2002). (Lin and Wang, 2008) discuss that as e-commerce becomes more mature, increased spending by existing online buyers has replaced new buyers coming on board as the main force fueling e-commerce sales. In other words, the growing e-commerce market size might not benefit all online retailers. Those who wish to succeed must take customers away from competitors, motivate those customers to spend more, and retain their loyalty. To reach these goals, advanced e-commerce technologies and innovative business models might provide the difference that makes some vendors more attractive than others. Some of the primary e- commerce technologies are auctions, negotiation, recommender systems and automated shopping (Lin and Wang, 2008). As we will discuss in section 1.1, business owners tend to attain customer’s loyalty, satisfaction and to improve their sale (cross-selling) by means of recommender systems. Therefore programmers try to develop intelligent and powerful websites to encourage the customers to buy more items which they need and feel satisfied by purchasing them. Such items might have been unseen by the customers due different aspects of IADIS International Conference e-Commerce 2008 199