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Constructing Varied and Attractive Shortlists from Databases: A Group Decision Approach

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Transactions on Computational Collective Intelligence XXXVII

Part of the book series: Lecture Notes in Computer Science ((TCCI,volume 13750))

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Abstract

Thanks to the Internet, basic information can be found about a very large number of offers at very little cost. Many sites give basic information about real estate offers, including price, size, location and number of rooms. Information of this kind is sufficient to assess whether an offer is potentially attractive or not, but does not suffice in making an ultimate decision. The number of real estate offers in a city may be very large. In such a case, it can be beneficial to use an automatic procedure to first eliminate offers that do not satisfy the basic criteria of an individual or family and then construct a shortlist of varied and potentially attractive offers. This article recalls an algorithm that derives such a shortlist for an individual searcher. The novelty of this article lies in adapting this algorithm to scenarios in which a group decision is made. A practical example based on real estate offers in Warsaw is used to illustrate the algorithm.

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Acknowledgements

This research was funded by Polish National Science Centre grant number 2018/29/B/HS4/02857, “Logistics, Trade and Consumer Decisions in the Age of the Internet”.

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Authors and Affiliations

  1. Department of Computer Science and Systems Engineering, Faculty of Computer Science and Telecommunications, Wrocław University of Science and Technology, Wrocław, Poland

    David M. Ramsey

  2. Department of Applied Computer Science, Faculty of Computer Science and Telecommunications, Wrocław University of Science and Technology, Wrocław, Poland

    Aleksander Mariański

Authors
  1. David M. Ramsey
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  2. Aleksander Mariański
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Corresponding author

Correspondence to David M. Ramsey .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Wroclaw University of Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  2. Faculty of Information and Communication Technology, Swinburne University of Technology, Hawthorn, Victoria, VIC, Australia

    Ryszard Kowalczyk

  3. WSB University in Wroclaw, Wroclaw, Poland

    Jacek Mercik

  4. University of Lower Silesia, Wroclaw, Poland

    Anna Motylska-Kuźma

Appendix: Spatial Distribution of Real Estate Offers

Appendix: Spatial Distribution of Real Estate Offers

Fig. 1.
figure 1

Spatial distribution (relative to the city centre) of real estate offers satisfying the first set of constraints regarding price (at most 500 000PLN), floorspace (at least 30 m\(^2\)) and number of rooms (at least two). There are 1602 such offers.

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Fig. 2.
figure 2

Spatial distribution (relative to the city centre) of real estate offers satisfying the second set of constraints regarding price (at most 650 000PLN), floorspace (at least 40 m\(^2\)) and number of rooms (at least two). There are 2927 such offers.

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Fig. 3.
figure 3

Spatial distribution (relative to the city centre) of real estate offers satisfying the third set of constraints regarding price (at most 750 000PLN), floorspace (at least 50 m\(^2\)) and number of rooms (at least two). There are 2360 such offers.

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Fig. 4.
figure 4

Spatial distribution (relative to the city centre) of real estate offers satisfying the fourth set of constraints regarding price (at most 900 000PLN), floorspace (at least 60 m\(^2\)) and number of rooms (at least three). There are 1693 such offers.

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Fig. 5.
figure 5

Spatial distribution (relative to the city centre) of real estate offers satisfying the fifth set of constraints regarding price (at most 1 000 000PLN), floorspace (at least 70 m\(^2\)) and number of rooms (at least three). There are 946 such offers.

Full size image

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Ramsey, D.M., Mariański, A. (2022). Constructing Varied and Attractive Shortlists from Databases: A Group Decision Approach. In: Nguyen, N.T., Kowalczyk, R., Mercik, J., Motylska-Kuźma, A. (eds) Transactions on Computational Collective Intelligence XXXVII. Lecture Notes in Computer Science(), vol 13750. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-66597-8_2

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  • DOI: https://doi.org/10.1007/978-3-662-66597-8_2

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