Preference-Search based Recommendation System for Accommodation Facilitator : A Review

Authors(3) :-Shristi Simran, Akash Pande, Prof. Payal Desai

Finding an online house or rented property that meet renters’ requirements is increasingly getting difficult due to large pool of choices available with the renters’ before finalizing accommodation. A renter may spend considerable amount of time exploring numerous online resources to locate accommodation that fit his requirements. Furthermore, renters may not always express their preferences in a manner that easily matches their requirements. Exploring and searching for accommodation online has been done mainly through database queries that return a list of the most suitable accommodations. Recommendation systems methods can be applied to smooth the task of finding desired and required accommodation online. This study proposes a recommendation system that enables renters to carry out a preference-based search on rental properties for accommodation. In this paper preference-based search technique is combined with method called as example-critiquing. Rather than executing a query against the database, this combined approach prompts the renters to express some preferences on rental properties for accommodation. Than this method will be used to construct a preference model for the user, and finally generates a list of properties that best match that preferences.

Authors and Affiliations

Shristi Simran
Computer Science and Engineering Department, Parul University, Vadodara, Gujarat, India
Akash Pande
Computer Science and Engineering Department, Parul University, Vadodara, Gujarat, India
Prof. Payal Desai
Computer Science and Engineering Department, Parul University, Vadodara, Gujarat, India

Accommodation, Renters, Preference-Based Search, Example-Critiquing, Recommendation System

  1. Viappiani, P., & Faltings, B., 2006: Design and Implementation of Preference-based Search, Ecole Polytechnique Fédérale de Lausanne, Artificial Intelligence Lab, Lausanne
  2. Ricci, F., Rokach, L., Shapira, B., & Kantor, P., 2011: Introduction to Recommender System Handbook. In Recommender System Handbook (pp. 1-35), Springer
  3. Yuan, X., Lee, J.-H., Kim, S.-J., & Kim, Y.-H., 2013: Toward a user- oriented recommendation system for real estate websites, Information Systems, 38(2), 231-243
  4. Hurley, G., & Wilson, D. C. (2001). DubLet: An Online CBR System for Rental Property Recommendation. In D. W. Aha, & I. Watson (Eds.), Case-Based Reasoning Research and Development (pp. 660-674). Springer Link.
  5. Sharma, R., & Singh, R. (2016, 05). Evolution of Recommender Systems from Ancient Time to Modern Era: A Survey. Indian Journal of Science and Technology, 9 (20), 1-12.
  6. Ekstrand, M., Riedl, T., & Konstan, J. (2010). Collaborative Filtering Recommender Systems. Foundations and Trends in Human-Computer Interaction, 4 (2), 81-173.
  7. Schafer, J., Konstan, J., & Riedl, J. (2001, 01). E-commerce Recommendation Applications. Data Mining and Knowledge Discovery, 5 (1), 115-153.
  8. Burke, R. D., 2002: Hybrid Recommender Systems: Survey and Experiments: User modeling and User-Adapted Interaction. The Journal of Personalization Research, 12(4), 331-370
  9. Felfernig, A., Friedrich, G., Jannach, D., & Zanker, M., 2011: Developping Constraint-based Recommenders. In F. Ricci, L. Rokach, B. Shapira, & P. B. Kantor, Recommender Systems Handbook, Springer.
  10. Pazzani, M. J. (1999). A Framework for Collaborative, Content-Based and Demographic Filtering. Artificial Intelligence Review, 13, 393-408.
  11. Karypis, G., Konstan, J., Sarwar, B., & Riedl, J. (2001). Item-Based Collaborative Filtering Recommendation Algorithms. 10th International World Wide Web Conference (pp. 285-295). Hong-Kong: WWW10.
  12. Chen, L., & Pu, P. (2012). Critiquing-based recommenders: survey and emerging trends. User Modeling and User-Adapted Interaction, 22 (1), 125-150.
  13. Pu, P., & Faltings, B. (2000). Enriching buyers’ experiences: the SmartClient approach. SIG- CHI Conference on Human Factors in Computing Systems (pp. 289-296). New York: ACM.
  14. Chen, L., & Pu, P., 2007: Preference-based Organisation Interfaces: Aiding User Critiques in Recommender Systems. In C. Conati, K. McCoy, & G. Paliouras (Eds.), User Modeling 2007: 11th International Conference (pp. 77-86), Springer Berlin Heidelberg

Publication Details

Published in : Volume 5 | Issue 2 | March-April 2019
Date of Publication : 2019-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 951-956
Manuscript Number : CSEIT1952245
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Shristi Simran, Akash Pande, Prof. Payal Desai, "Preference-Search based Recommendation System for Accommodation Facilitator : A Review", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.951-956, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT1952245
Journal URL : https://res.ijsrcseit.com/CSEIT1952245 Citation Detection and Elimination     |      |          | BibTeX | RIS | CSV

Article Preview