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

Applied Mathematics and Nonlinear Sciences

Ahmed Aldeeb Hooreya Mohamed¹  Ma Zhaoheng²  Huo Zheng³  Xing Wentao⁴  Wu Yanbin⁵ 

[1] Applied Science University, Kingdom of Bahrain;Hebei Yunteng surveying and Mapping Technology Service Co., Ltd, Shijiazhuang, 050000, Hebei Province;Information Technology School, Hebei University of Economics and Business, Shijiazhuang, 050061, Hebei Province, China;Land Development and Consolidation Center of Haixing County, Cangzhou, 061200, Hebei Province, China;Management Science and Engineering School, Hebei University of Economics and Business, Shijiazhuang, 050061, Hebei Province, China;

关键词: industrial and mining wasteland reclamation;    industrial tourism;    user profile;    recommender system;   

DOI  :  10.2478/amns.2021.2.00039

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown