Identifying the Relatedness between Tourism Attractions from Online Reviews with Heterogeneous Information Network Embedding
The relatedness between tourism attractions can be used in a variety of tourism applications, such as destination collaboration, commercial marketing, travel recommendations, and so on. Existing studies have identified the relatedness between attractions through measuring their co-occurrence—these a...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/10/12/797 |
| _version_ | 1797503941777293312 |
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| author | Peiyuan Qiu Jialiang Gao Feng Lu |
| author_facet | Peiyuan Qiu Jialiang Gao Feng Lu |
| author_sort | Peiyuan Qiu |
| collection | DOAJ |
| description | The relatedness between tourism attractions can be used in a variety of tourism applications, such as destination collaboration, commercial marketing, travel recommendations, and so on. Existing studies have identified the relatedness between attractions through measuring their co-occurrence—these attractions are mentioned in a text at the same time—extracted from online tourism reviews. However, the implicit semantic information in these reviews, which definitely contributes to modelling the relatedness from a more comprehensive perspective, is ignored due to the difficulty of quantifying the importance of different dimensions of information and fusing them. In this study, we considered both the co-occurrence and images of attractions and introduce a heterogeneous information network (HIN) to reorganize the online reviews representing this information, and then used HIN embedding to comprehensively identify the relatedness between attractions. First, an online review-oriented HIN was designed to form the different types of elements in the reviews. Second, a topic model was employed to extract the nodes of the HIN from the review texts. Third, an HIN embedding model was used to capture the semantics in the HIN, which comprehensively represents the attractions with low-dimensional vectors. Finally, the relatedness between attractions was identified by calculating the similarity of their vectors. The method was validated with mass tourism reviews from the popular online platform MaFengWo. It is argued that the proposed HIN effectively expresses the semantics of attraction co-occurrences and attraction images in reviews, and the HIN embedding captures the differences in these semantics, which facilitates the identification of the relatedness between attractions. |
| first_indexed | 2024-03-10T03:57:34Z |
| format | Article |
| id | doaj.art-83939fcfa640427ca8aa328488036ac8 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T03:57:34Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-83939fcfa640427ca8aa328488036ac82023-11-23T08:41:41ZengMDPI AGISPRS International Journal of Geo-Information2220-99642021-11-01101279710.3390/ijgi10120797Identifying the Relatedness between Tourism Attractions from Online Reviews with Heterogeneous Information Network EmbeddingPeiyuan Qiu0Jialiang Gao1Feng Lu2School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, ChinaState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaThe relatedness between tourism attractions can be used in a variety of tourism applications, such as destination collaboration, commercial marketing, travel recommendations, and so on. Existing studies have identified the relatedness between attractions through measuring their co-occurrence—these attractions are mentioned in a text at the same time—extracted from online tourism reviews. However, the implicit semantic information in these reviews, which definitely contributes to modelling the relatedness from a more comprehensive perspective, is ignored due to the difficulty of quantifying the importance of different dimensions of information and fusing them. In this study, we considered both the co-occurrence and images of attractions and introduce a heterogeneous information network (HIN) to reorganize the online reviews representing this information, and then used HIN embedding to comprehensively identify the relatedness between attractions. First, an online review-oriented HIN was designed to form the different types of elements in the reviews. Second, a topic model was employed to extract the nodes of the HIN from the review texts. Third, an HIN embedding model was used to capture the semantics in the HIN, which comprehensively represents the attractions with low-dimensional vectors. Finally, the relatedness between attractions was identified by calculating the similarity of their vectors. The method was validated with mass tourism reviews from the popular online platform MaFengWo. It is argued that the proposed HIN effectively expresses the semantics of attraction co-occurrences and attraction images in reviews, and the HIN embedding captures the differences in these semantics, which facilitates the identification of the relatedness between attractions.https://www.mdpi.com/2220-9964/10/12/797relatedness between attractionsonline tourism reviewsheterogeneous information networkembeddingattraction imagetopic extraction |
| spellingShingle | Peiyuan Qiu Jialiang Gao Feng Lu Identifying the Relatedness between Tourism Attractions from Online Reviews with Heterogeneous Information Network Embedding ISPRS International Journal of Geo-Information relatedness between attractions online tourism reviews heterogeneous information network embedding attraction image topic extraction |
| title | Identifying the Relatedness between Tourism Attractions from Online Reviews with Heterogeneous Information Network Embedding |
| title_full | Identifying the Relatedness between Tourism Attractions from Online Reviews with Heterogeneous Information Network Embedding |
| title_fullStr | Identifying the Relatedness between Tourism Attractions from Online Reviews with Heterogeneous Information Network Embedding |
| title_full_unstemmed | Identifying the Relatedness between Tourism Attractions from Online Reviews with Heterogeneous Information Network Embedding |
| title_short | Identifying the Relatedness between Tourism Attractions from Online Reviews with Heterogeneous Information Network Embedding |
| title_sort | identifying the relatedness between tourism attractions from online reviews with heterogeneous information network embedding |
| topic | relatedness between attractions online tourism reviews heterogeneous information network embedding attraction image topic extraction |
| url | https://www.mdpi.com/2220-9964/10/12/797 |
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