Identifying the Relatedness between Tourism Attractions from Online Reviews with Heterogeneous Information Network Embedding
文献类型：期刊论文
| 作者 | Qiu, Peiyuan1,3; Gao, Jialiang3,4; Lu, Feng2,3,4,5 |
| 刊名 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
 |
| 出版日期 | 2021-12-01 |
| 卷号 | 10期号:12页码:20 |
| 关键词 | relatedness between attractions online tourism reviews heterogeneous information network embedding attraction image topic extraction |
| DOI | 10.3390/ijgi10120797 |
| 通讯作者 | Lu, Feng(luf@lreis.ac.cn) |
| 英文摘要 | 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. |
| WOS研究方向 | Computer Science ; Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000744022400001 |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/169875]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Lu, Feng |
| 作者单位 | 1.Shandong Jianzhu Univ, Sch Surveying & Geoinformat, Jinan 250101, Peoples R China 2.Fuzhou Univ, Acad Digital China, Fuzhou 350002, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing NANJING, Peoples R China |
| 推荐引用方式 GB/T 7714 | Qiu, Peiyuan,Gao, Jialiang,Lu, Feng. Identifying the Relatedness between Tourism Attractions from Online Reviews with Heterogeneous Information Network Embedding[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2021,10(12):20. |
| APA | Qiu, Peiyuan,Gao, Jialiang,&Lu, Feng.(2021).Identifying the Relatedness between Tourism Attractions from Online Reviews with Heterogeneous Information Network Embedding.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,10(12),20. |
| MLA | Qiu, Peiyuan,et al."Identifying the Relatedness between Tourism Attractions from Online Reviews with Heterogeneous Information Network Embedding".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 10.12(2021):20. |
入库方式： OAI收割
来源：地理科学与资源研究所
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