Intelligent Tourism Personalized Recommendation Based on Multi-Fusion of Clustering Algorithms
Actual tourism mining models are often used to discover potential information in documents, but tourism models without human knowledge often produce unexplainable topics. This paper combines big data technology to build a personalized recommendation system for smart tourism, model the contextual inf...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Advances in Multimedia |
| Online Access: | http://dx.doi.org/10.1155/2021/4517973 |
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| _version_ | 1832559211167350784 |
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| author | HongYan Liang |
| author_facet | HongYan Liang |
| author_sort | HongYan Liang |
| collection | DOAJ |
| description | Actual tourism mining models are often used to discover potential information in documents, but tourism models without human knowledge often produce unexplainable topics. This paper combines big data technology to build a personalized recommendation system for smart tourism, model the contextual information usage ontology under the tourism information system, and give the association between various ontologies. Then, this paper uses a matrix to describe each discrete attribute and interval attribute and uses a vector to model the user’s preferences. In addition, this paper constructs an intelligent recommendation system based on the actual needs of travel recommendation and verifies the system in combination with experimental research. Through experimental analysis, it can be known that the intelligent tourism personalized recommendation system based on big data technology proposed in this paper has a high practical effect. |
| format | Article |
| id | doaj-art-5eebdef98b8141c0b131bce3a7e1c999 |
| institution | Kabale University |
| issn | 1687-5699 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Multimedia |
| spelling | doaj-art-5eebdef98b8141c0b131bce3a7e1c9992025-02-03T01:30:33ZengWileyAdvances in Multimedia1687-56992021-01-01202110.1155/2021/4517973Intelligent Tourism Personalized Recommendation Based on Multi-Fusion of Clustering AlgorithmsHongYan Liang0Xinyang Vocational and Technical CollegeActual tourism mining models are often used to discover potential information in documents, but tourism models without human knowledge often produce unexplainable topics. This paper combines big data technology to build a personalized recommendation system for smart tourism, model the contextual information usage ontology under the tourism information system, and give the association between various ontologies. Then, this paper uses a matrix to describe each discrete attribute and interval attribute and uses a vector to model the user’s preferences. In addition, this paper constructs an intelligent recommendation system based on the actual needs of travel recommendation and verifies the system in combination with experimental research. Through experimental analysis, it can be known that the intelligent tourism personalized recommendation system based on big data technology proposed in this paper has a high practical effect.http://dx.doi.org/10.1155/2021/4517973 |
| spellingShingle | HongYan Liang Intelligent Tourism Personalized Recommendation Based on Multi-Fusion of Clustering Algorithms Advances in Multimedia |
| title | Intelligent Tourism Personalized Recommendation Based on Multi-Fusion of Clustering Algorithms |
| title_full | Intelligent Tourism Personalized Recommendation Based on Multi-Fusion of Clustering Algorithms |
| title_fullStr | Intelligent Tourism Personalized Recommendation Based on Multi-Fusion of Clustering Algorithms |
| title_full_unstemmed | Intelligent Tourism Personalized Recommendation Based on Multi-Fusion of Clustering Algorithms |
| title_short | Intelligent Tourism Personalized Recommendation Based on Multi-Fusion of Clustering Algorithms |
| title_sort | intelligent tourism personalized recommendation based on multi fusion of clustering algorithms |
| url | http://dx.doi.org/10.1155/2021/4517973 |
| work_keys_str_mv | AT hongyanliang intelligenttourismpersonalizedrecommendationbasedonmultifusionofclusteringalgorithms |