چكيده به لاتين
Nowadays, the tourism industry after the oil and automotive industry has become the third largest industry in the world to generate income and employment. Rural tourism and agricultural tourism are the branches of this industry, which development contributes to the economic growth of rural communities, nomadic populations and farmers. One of the problems in this branch of tourism is the lack of knowledge of the people and tourists about these attractions. In today's world, the use of information technology to develop the tourism industry, including rural tourism and agricultural tourism, is essential. IT-based tools that can be used to introduce and enhance tourism are social networks and recommender systems.
Recommendation systems provide users with suggestions that increase user awareness and facilitate their decision making. Social Recommender systems, in addition to information about users and tourist attractions, use social networking information such as list of friends, likes and others' choices to offer users.
There are several methods to create a recommendation system, including cumulative smoothing, content-based methods, and field-based methods. In each industry, one or more of the methods used is a hybrid approach. Also, in each industry, different criteria for proposing proposals are considered.
In this thesis, by reviewing articles, books, websites and consulting with experts, the factors and criteria used in a social recommendation system for rural tourism and agriculture tourism are used to recommend tourist attractions to tourists, and then these recommendations by using SPSS software and Friedman method, has been analyzed and prioritized. Also, the methods used to present the recommend from the tourists' perspective were prioritized with Expert Choice software and the AHP method.
Keywords: Rural and Agriculture Tourism, social networks, recommender systems, Social Recommender systems
