Popularity prediction on vacation rental websites
In the personal house renting scenario, customers usually make quick assessments based on previous customers' reviews, which makes such reviews essential for the business. If the house is assessed as popular, a Matthew effect will be observed as more people will be willing to book it. Due to th...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/160974 |
| _version_ | 1811680194796191744 |
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| author | Li, Yang Wang, Suhang Ma, Yukun Pan, Quan Cambria, Erik |
| author2 | School of Computer Science and Engineering |
| author_facet | School of Computer Science and Engineering Li, Yang Wang, Suhang Ma, Yukun Pan, Quan Cambria, Erik |
| author_sort | Li, Yang |
| collection | NTU |
| description | In the personal house renting scenario, customers usually make quick assessments based on previous customers' reviews, which makes such reviews essential for the business. If the house is assessed as popular, a Matthew effect will be observed as more people will be willing to book it. Due to the lack of definition and quantity assessment measures, however, it is difficult to make a popularity evaluation and prediction. To solve this problem, the concept of house popularity is well defined in this paper. Specifically, the house popularity is decided by inter-event timeand rating score at the same time. To make a more effective prediction over these two correlated variables, a dual-gated recurrent unit (DGRU) is employed. Furthermore, an encoder-decoder framework with DGRU is proposed to perform popularity prediction. Empirical results show the effectiveness of the proposed DGRU and the encoder-decoder framework in two-correlated sequences prediction and popularity prediction, respectively. |
| first_indexed | 2024-10-01T03:21:11Z |
| format | Journal Article |
| id | ntu-10356/160974 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:21:11Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1609742022-08-10T02:19:32Z Popularity prediction on vacation rental websites Li, Yang Wang, Suhang Ma, Yukun Pan, Quan Cambria, Erik School of Computer Science and Engineering Engineering::Computer science and engineering Vacation Rental Websites Popularity Prediction In the personal house renting scenario, customers usually make quick assessments based on previous customers' reviews, which makes such reviews essential for the business. If the house is assessed as popular, a Matthew effect will be observed as more people will be willing to book it. Due to the lack of definition and quantity assessment measures, however, it is difficult to make a popularity evaluation and prediction. To solve this problem, the concept of house popularity is well defined in this paper. Specifically, the house popularity is decided by inter-event timeand rating score at the same time. To make a more effective prediction over these two correlated variables, a dual-gated recurrent unit (DGRU) is employed. Furthermore, an encoder-decoder framework with DGRU is proposed to perform popularity prediction. Empirical results show the effectiveness of the proposed DGRU and the encoder-decoder framework in two-correlated sequences prediction and popularity prediction, respectively. Agency for Science, Technology and Research (A*STAR) This research is supported by the Agency for Science, Technology and Research (A*STAR) under its AME Programmatic Funding Scheme (Project #A18A2b0046). 2022-08-10T02:19:32Z 2022-08-10T02:19:32Z 2020 Journal Article Li, Y., Wang, S., Ma, Y., Pan, Q. & Cambria, E. (2020). Popularity prediction on vacation rental websites. Neurocomputing, 412, 372-380. https://dx.doi.org/10.1016/j.neucom.2020.05.092 0925-2312 https://hdl.handle.net/10356/160974 10.1016/j.neucom.2020.05.092 2-s2.0-85087915003 412 372 380 en A18A2b0046 Neurocomputing © 2020 Elsevier B.V. All rights reserved. |
| spellingShingle | Engineering::Computer science and engineering Vacation Rental Websites Popularity Prediction Li, Yang Wang, Suhang Ma, Yukun Pan, Quan Cambria, Erik Popularity prediction on vacation rental websites |
| title | Popularity prediction on vacation rental websites |
| title_full | Popularity prediction on vacation rental websites |
| title_fullStr | Popularity prediction on vacation rental websites |
| title_full_unstemmed | Popularity prediction on vacation rental websites |
| title_short | Popularity prediction on vacation rental websites |
| title_sort | popularity prediction on vacation rental websites |
| topic | Engineering::Computer science and engineering Vacation Rental Websites Popularity Prediction |
| url | https://hdl.handle.net/10356/160974 |
| work_keys_str_mv | AT liyang popularitypredictiononvacationrentalwebsites AT wangsuhang popularitypredictiononvacationrentalwebsites AT mayukun popularitypredictiononvacationrentalwebsites AT panquan popularitypredictiononvacationrentalwebsites AT cambriaerik popularitypredictiononvacationrentalwebsites |