DoRA: Domain-Based Self-Supervised Learning Framework for Low-Resource Real Estate Appraisal-Reference-Cited by-同舟云学术

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DoRA: Domain-Based Self-Supervised Learning Framework for Low-Resource Real Estate Appraisal

Published:2023-10-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
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Author:

Du Wei-Wei¹^ORCID,Wang Wei-Yao¹^ORCID,Peng Wen-Chih¹^ORCID

Affiliation:

1. National Yang Ming Chiao Tung University, Hsinchu, Taiwan Roc

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3583780.3615470

Reference29 articles.

1. Using ridge regression with genetic algorithm to enhance real estate appraisal forecasting

2. Sercan Ö. Arik and Tomas Pfister . 2021 . TabNet: Attentive Interpretable Tabular Learning. In AAAI. AAAI Press , 6679--6687. Sercan Ö. Arik and Tomas Pfister. 2021. TabNet: Attentive Interpretable Tabular Learning. In AAAI. AAAI Press, 6679--6687.

3. House price prediction using clustering and genetic programming along with conducting a comparative study

4. Attention-based multi-modal fusion for improved real estate appraisal: a case study in Los Angeles

5. Tianqi Chen and Carlos Guestrin. 2016. XGBoost: A Scalable Tree Boosting System. In KDD. ACM 785--794. Tianqi Chen and Carlos Guestrin. 2016. XGBoost: A Scalable Tree Boosting System. In KDD. ACM 785--794.

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