Optimization of Tourism Information Analysis System Based on Big Data Algorithm
On the basis of ecological footprint theory and tourism ecological footprint theory, the sustainable development indexes such as ecological footprint, ecological carrying capacity, ecological deficit, and ecological surplus of the research area were calculated and the long-term change pattern of eac...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/8841419 |
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| _version_ | 1832554568354889728 |
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| author | Jing Yang Bing Zheng Zhenghua Chen |
| author_facet | Jing Yang Bing Zheng Zhenghua Chen |
| author_sort | Jing Yang |
| collection | DOAJ |
| description | On the basis of ecological footprint theory and tourism ecological footprint theory, the sustainable development indexes such as ecological footprint, ecological carrying capacity, ecological deficit, and ecological surplus of the research area were calculated and the long-term change pattern of each index was analyzed. This paper shows that the ecological footprint of the research area increases year by year, but the ecological footprint is always smaller than the ecological carrying capacity, indicating that the area is still in the state of sustainable development. However, the per capita ecological surplus shows a decreasing trend year by year, indicating that the sustainable development of the region is getting worse. This paper proposes a reordering method of tourist attractions based on heterogeneous information fusion, and realizes the retrieval and reordering of tourist attractions based on user query and fusion of heterogeneous information, so as to help users make travel decisions. In view of the shortage of tourism commercial websites to passively provide scenic spot information, this paper puts forward a scenic spot retrieval method based on query words to enable users to obtain scenic spot information according to their needs, and constructs a tourist consumer data analysis system. The preprocessing methods and methods adopted by the data preprocessing module are analyzed in detail, and the algorithms used in the travel route analysis and consumer spending ability analysis are described in detail. The data of tourism consumers are analyzed by this system, and the results are evaluated. |
| format | Article |
| id | doaj-art-5ff1a7edf8524c59885b0c37c575bc03 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-5ff1a7edf8524c59885b0c37c575bc032025-02-03T05:51:11ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/88414198841419Optimization of Tourism Information Analysis System Based on Big Data AlgorithmJing Yang0Bing Zheng1Zhenghua Chen2School of Information Engineering, Hainan Vocational University of Science and Technology, Haikou 571126, ChinaSchool of Information Engineering, Hainan Vocational University of Science and Technology, Haikou 571126, ChinaSchool of of Finance and Economics, Hainan Vocational University of Science and Technology, Haikou 571126, ChinaOn the basis of ecological footprint theory and tourism ecological footprint theory, the sustainable development indexes such as ecological footprint, ecological carrying capacity, ecological deficit, and ecological surplus of the research area were calculated and the long-term change pattern of each index was analyzed. This paper shows that the ecological footprint of the research area increases year by year, but the ecological footprint is always smaller than the ecological carrying capacity, indicating that the area is still in the state of sustainable development. However, the per capita ecological surplus shows a decreasing trend year by year, indicating that the sustainable development of the region is getting worse. This paper proposes a reordering method of tourist attractions based on heterogeneous information fusion, and realizes the retrieval and reordering of tourist attractions based on user query and fusion of heterogeneous information, so as to help users make travel decisions. In view of the shortage of tourism commercial websites to passively provide scenic spot information, this paper puts forward a scenic spot retrieval method based on query words to enable users to obtain scenic spot information according to their needs, and constructs a tourist consumer data analysis system. The preprocessing methods and methods adopted by the data preprocessing module are analyzed in detail, and the algorithms used in the travel route analysis and consumer spending ability analysis are described in detail. The data of tourism consumers are analyzed by this system, and the results are evaluated.http://dx.doi.org/10.1155/2020/8841419 |
| spellingShingle | Jing Yang Bing Zheng Zhenghua Chen Optimization of Tourism Information Analysis System Based on Big Data Algorithm Complexity |
| title | Optimization of Tourism Information Analysis System Based on Big Data Algorithm |
| title_full | Optimization of Tourism Information Analysis System Based on Big Data Algorithm |
| title_fullStr | Optimization of Tourism Information Analysis System Based on Big Data Algorithm |
| title_full_unstemmed | Optimization of Tourism Information Analysis System Based on Big Data Algorithm |
| title_short | Optimization of Tourism Information Analysis System Based on Big Data Algorithm |
| title_sort | optimization of tourism information analysis system based on big data algorithm |
| url | http://dx.doi.org/10.1155/2020/8841419 |
| work_keys_str_mv | AT jingyang optimizationoftourisminformationanalysissystembasedonbigdataalgorithm AT bingzheng optimizationoftourisminformationanalysissystembasedonbigdataalgorithm AT zhenghuachen optimizationoftourisminformationanalysissystembasedonbigdataalgorithm |