Lexicographic criteria for ranking opportunity sets with similarities
Bibliographic Data
| ID | 11284698 |
|---|---|
| Authors | Carmen Vázquez (0000-0002-9554-3926, Universidade de Vigo, corresponding author) |
| Year | 2022 |
| Volume | 117 |
| Pages | 1-5 |
| Publication date | 2022-05-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Mathematical Social Sciences (JOURNAL) |
| Journal identifiers | ISSN: 0165-4896 • E-ISSN: 1879-3118 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.mathsocsci.2022.02.001 |
| OpenAlex | W4213428757 |
| Language | EN |
| References cited | 15 |
The aim of this paper is to provide two lexicographic-based orderings particularly suitable for ranking very large opportunity sets. We use a similarity relation to slim down very large opportunity sets while preserving the quality and variety of their alternatives. Two different lexicographic criteria, both of which have been characterized and contrasted, are then applied to rank these sets
Combinatorics · Data mining · Information retrieval · Lexicographical order · Mathematical economics · Quality (philosophy · Rank (graph theory · Ranking (information retrieval · Relation (database · Similarity (geometry · Statistics · Variety (cybernetics · Bayesian Modeling and Causal Inference · Computer Science · Mathematics · Multi-Criteria Decision Making · Organizational Management and Leadership · Artificial Intelligence
| Citation velocity | historical |
|---|---|
| Highly cited | No |