Precision Marketing Strategy for Ecotourism Based on Data Mining and User Images

Abstract

With the continuous development of ecotourism industry, it has become a common concern in ecotourism industry to utilize the available data to realize the change of ecotourism industry and promote the product development and business expansion of ecotourism industry. To this end, we propose a personalized ecotourism route recommendation (PTIR) algorithm based on the popularity of points of interest (POI) and users’ interest preferences. First, we analyze the real historical ecotourism footprints of users, propose a time-based user interest preference, and design a method to calculate the best ecotourism route given the travel time limit, departure point, and end point. Experiments were conducted on a real dataset of the Flickr social networking site, and the results showed that this personalized ecotourism route recommendation algorithm has greatly improved accuracy and recall compared with the traditional algorithm that only considers POI popularity, and the results were visualized through specific experimental cases based on user image clustering.