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Relevant bibliographies by topics / Euclidean preferences

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Journal articles

Academic literature on the topic 'Euclidean preferences'

Author: Grafiati

Published: 25 May 2024

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Journal articles on the topic "Euclidean preferences"

1

Bogomolnaia, Anna, and Jean-François Laslier. "Euclidean preferences." Journal of Mathematical Economics 43, no. 2 (2007): 87–98. http://dx.doi.org/10.1016/j.jmateco.2006.09.004.

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2

Luaces, Oscar, Jorge Díez, Thorsten Joachims, and Antonio Bahamonde. "Mapping preferences into Euclidean space." Expert Systems with Applications 42, no. 22 (2015): 8588–96. http://dx.doi.org/10.1016/j.eswa.2015.07.013.

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3

Conroy-Beam, Daniel. "Euclidean Mate Value and Power of Choice on the Mating Market." Personality and Social Psychology Bulletin 44, no. 2 (2017): 252–64. http://dx.doi.org/10.1177/0146167217739262.

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Three studies tested the hypothesis that human mate choice psychology uses a Euclidean algorithm to integrate mate preferences into estimates of mate value. In Study 1, a series of agent-based models identify a pattern of results relatively unique to mating markets where individuals high in Euclidean mate value experience greater power of choice: strong preference fulfillment overall and correlations between mate value and (a) preference fulfillment, (b) ideal standards, and (c) partner mate value. Studies 2 and 3 demonstrated that this pattern of results that emerges in human romantic relatio

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4

Bordes, Georges, Gilbert Laffond, and Michel Le Breton. "Euclidean preferences, option sets and strategyproofness." SERIEs 2, no. 4 (2011): 469–83. http://dx.doi.org/10.1007/s13209-011-0075-2.

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5

Richter, Michael, and Ariel Rubinstein. "Convex preferences: A new definition." Theoretical Economics 14, no. 4 (2019): 1169–83. http://dx.doi.org/10.3982/te3286.

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We suggest a concept of convexity of preferences that does not rely on any algebraic structure. A decision maker has in mind a set of orderings interpreted as evaluation criteria. A preference relation is defined to be convex when it satisfies the following condition: If, for each criterion, there is an element that is both inferior to b by the criterion and superior to a by the preference relation, then b is preferred to a. This definition generalizes the standard Euclidean definition of convex preferences. It is shown that under general conditions, any strict convex preference relation is re

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6

Mutlu, Güneş, and Ahmet Mete Çilingirtürk. "Social Network of Faculties According to Student Preferences in Transition to Higher Education." Lietuvos statistikos darbai 51, no. 1 (2012): 51–56. http://dx.doi.org/10.15388/ljs.2012.13905.

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In social network analysis, the studies on weighted adjacency matrix of nodes are increasing day by day. In thispaper, a method is proposed by including node properties to neighbourhood matrix, in order to see the structures of weightedadjacency matrix that defines the relationship between the nodes. In accordance with this proposal, the relationship betweenthe faculties of Turkish universities is studied according to student preferences. Weighted adjacency matrix between facultiesis composed based on the frequency of faculty preference of students. By using the properties of faculties, this m

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7

Liu, Chunyang, Chao Liu, Haiqiang Xin, Jian Wang, Jiping Liu, and Shenghua Xu. "Joint Geosequential Preference and Distance Metric Factorization for Point-of-Interest Recommendation." Mathematical Problems in Engineering 2020 (October 30, 2020): 1–14. http://dx.doi.org/10.1155/2020/6582676.

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Point-of-interest (POI) recommendation is a valuable service to help users discover attractive locations in location-based social networks (LBSNs). It focuses on capturing users’ movement patterns and location preferences by using massive historical check-in data. In the past decade, matrix factorization has become a mature and widely used technology in POI recommendation. However, the inner product of latent vectors adopted in matrix factorization methods does not satisfy the triangle inequality property, which may limit the expressiveness and lead to suboptimal solutions. Besides, the extrem

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8

Azrieli, Yaron. "Axioms for Euclidean preferences with a valence dimension." Journal of Mathematical Economics 47, no. 4-5 (2011): 545–53. http://dx.doi.org/10.1016/j.jmateco.2011.07.004.

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9

Henry, Marc, and Ismael Mourifié. "EUCLIDEAN REVEALED PREFERENCES: TESTING THE SPATIAL VOTING MODEL." Journal of Applied Econometrics 28, no. 4 (2011): 650–66. http://dx.doi.org/10.1002/jae.1276.

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10

Blasco, Xavier, Gilberto Reynoso-Meza, Enrique A. Sánchez-Pérez, Juan Vicente Sánchez-Pérez, and Natalia Jonard-Pérez. "A Simple Proposal for Including Designer Preferences in Multi-Objective Optimization Problems." Mathematics 9, no. 9 (2021): 991. http://dx.doi.org/10.3390/math9090991.

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Including designer preferences in every phase of the resolution of a multi-objective optimization problem is a fundamental issue to achieve a good quality in the final solution. To consider preferences, the proposal of this paper is based on the definition of what we call a preference basis that shows the preferred optimization directions in the objective space. Associated to this preference basis a new basis in the objective space—dominance basis—is computed. With this new basis the meaning of dominance is reinterpreted to include the designer’s preferences. In this paper, we show the effect

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