Open AccessApplication of experience economy and recommendation algorithm in tourism reuse of industrial wasteland
Author(s) -
Yabin Wu,
Haibin Zheng,
Wentao Xing,
Zhaoheng Ma,
Hooreya Mohamed Ahmed Aldeeb
Publication year - 2021
Publication title -
applied mathematics and nonlinear sciences
Language(s) - English
Resource type - Journals
ISSN - 2444-8656
DOI - 10.2478/amns.2021.2.00039
Subject(s) - reuse , tourism , novelty , computer science , algorithm , recommender system , homogeneous , business , engineering , world wide web , mathematics , political science , philosophy , theology , combinatorics , law , waste management
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.