A Latent Space Model for Rank Data
نویسندگان
چکیده
Proportional representation by means of a single transferable vote (PR-STV) is the electoral system employed in Irish elections. In this system, voters rank some or all of the candidates in order of preference. A latent space model is proposed for these election data where both candidates and voters are located in the same D-dimensional space. The locations are determined by the ranked preferences which are modeled using the Plackett-Luce model for rank data. Voter positions reflect their preferences while the candidate locations represent the global view of the candidates by the electorate.
منابع مشابه
Identification of discrete concentration graph models with one hidden binary variable
Conditions are presented for different types of identifiability of discrete variable models generated over an undirected graph in which one node represents a binary hidden variable. These models can be seen as extensions of the latent class model to allow for conditional associations between the observable random variables. Since local identification corresponds to full rank of the parametrizat...
متن کاملBayesian Sparse Tucker Models for Dimension Reduction and Tensor Completion
Tucker decomposition is the cornerstone of modern machine learning on tensorial data analysis, which have attracted considerable attention for multiway feature extraction, compressive sensing, and tensor completion. The most challenging problem is related to determination of model complexity (i.e., multilinear rank), especially when noise and missing data are present. In addition, existing meth...
متن کاملCross-Domain Ranking via Latent Space Learning
We study the problem of cross-domain ranking, which addresses learning to rank objects from multiple interrelated domains. In many applications, we may have multiple interrelated domains, some of them with a large amount of training data and others with very little. We often wish to utilize the training data from all these related domains to help improve ranking performance. In this paper, we p...
متن کاملOrdinal Embedding with a Latent Factor Model
Constructing low-dimensional embeddings based on ordinal measurements has been a subject of significant recent interest, motivated in part by machine learning applications using human input in a robust way. Recent work has focused on observations of comparisons on distances between objects. We consider a different model where the embedding is formed within a latent space of factors upon which a...
متن کاملTHE APPLICATION OF DATA ENVELOPMENT ANALYSIS METHODOLOGY TO IMPROVE THE BENCHMARKING PROCESS IN THE EFQM BUSINESS MODEL (CASE STUDY: AUTOMOTIVE INDUSTRY OF IRAN)
This paper reports a survey and case study research outcomes on the application of Data Envelopment Analysis (DEA) to the ranking method of European Foundation for Quality Management (EFQM) Business Excellence Model in Iran’s Automotive Industry and improving benchmarking process after assessment. Following the global trend, the Iranian industry leaders have introduced the EFQM practice to thei...
متن کامل