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Data mining of travelers' travel patterns using voluntary location information (Case study: Tehran)
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Ensiyeh Mihanparast *   1, Javad Sadidi1 |
| 1- kharazmi University |
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Abstract: (554 Views) |
| Considering the travels of travelers in Tehran and identifying the most visited places according to the interests of tourists, the present study is in line with data mining the behavioral pattern of travelers' travel. In this regard, the purpose of this study is to identify the most visited places of travelers in Tehran based on their behavior for tourism purposes so that with the help of these models, their travel pattern can be studied and evaluated based on voluntary geographical information. For this purpose, data mining and RFM model have been used to analyze the relationships between passengers' characteristics and their desires. In this regard, in order to carry out the operational steps of the research, an application can be installed on the mobile phone and a data storage server sent by the tourist, which was prepared by the researcher and is available to tourists in Tehran in the next step. After storing voluntary geographical data by the tourist, according to the latest tourism statistics, about 85% of the most visited places in Tehran province, according to the tastes and visits of tourists, which includes religious, recreational, cultural-historical, scientific and social trips. According to the information obtained, it was found that the process of introducing the tourist area and directing tourists to the most visited places with the operational plans implemented in this section has been completed. In this situation, the recorded data of tourists is of great importance. In the RFM model, the types of trips, the number of places visited and tourist information are examined, and by identifying the existing data structure, the received data are matched with the variables of the date of visiting the place. Date of visiting the place) R and (duration of visiting the place) M and number of visits to the place (repeated visits to the place) F. Analysis of research data is not possible according to the three indicators of conventional statistical methods. The RFM method allows the researcher to cluster and analyze data to achieve the tourist travel pattern and is a suitable model for data analysis. The results of the study indicate that according to the interests of tourists in Tehran, recreational places are at the top of the pyramid, which are called based on the CLV calculated in the platinum study, and cultural, historical, religious and pilgrimage places are in the second place of silver and social places in the second degree. Third are the places called Messi, which indicate the importance of the places visited by tourists. It should be noted that in order to introduce the most visited places to other tourists, the tourism system of Tehran province can be used to attract tourists to this type of places. |
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| Keywords: Voluntary geographic information - Travel pattern - Data mining - Tourism - RFM method |
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Full-Text [PDF 1187 kb]
(143 Downloads)
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Type of Study: Research |
Subject:
Special
Received: 2021/04/24 | Accepted: 2021/11/17 | Published: 2024/04/30
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