Application of experience economy and recommendation algorithm in tourism reuse of industrial wasteland

Abstract

Industrial tourism is an important way for reuse of industrial wasteland. However, in China, reuse of industrial wasteland remain is in the exploratory practice stage, with problems such as lack of systematic planning, homogeneous strategies and inaccurate positioning of target customers. In this paper, we propose a method to reuse industrial wasteland by the combination of experience economy and recommendation algorithm. The industrial tourism product development direction is defined in the planning and design stage. The most relevant tourist-related features are extracted by establishing user profiles and experience economy-based questionnaires. The user-profile-based recommendation system generates a list of recommended tourist attractions. Finally, the recommendation-user-tag-project (R-UTP) algorithm is proposed and experimentally compared with UserkNN and ItemkNN algorithms. The R-UPT algorithm exhibits higher accuracy and has obvious advantages on recall ratio and novelty.