Positional scoring rules are often used for rank aggregation. In this work we study how scoring rules can be formulated as the minimization of some distance measures between rankings, and we also consider a new family of aggregation methods, called biased scoring rules. This work extends a previous known observation connecting Borda count with the minimization of the sum of the Spearman distanc...

This paper presents a novel method for multi-relational classification via an aggregation-based Inductive Logic Programming (ILP) approach. We extend the classical ILP representation by aggregation of multiple-features which aid the classification process by allowing for the analysis of relationships and dependencies between different features. In order to efficiently learn rules of this rich f...

Consumers have been banking and trading online for several years now. More ambitious and tech savvy consumers have also been constructing an overview of their financial life by using Personal Finance software like Quicken and online tools such as Yodlee and Mint.com. Since late 1999, Personal Financial Aggregators (PFAs) have started offering internet based services to automate this process of ...

This paper proposes and characterizes a sequential decision aggregation system consisting of agents performing binary sequential hypothesis testing, and a fusion center which collects the individual decisions and reaches the global decision according to some threshold rule. Individual decision makers’ behaviors in the system are influenced by other decision makers, through a model for social pr...

This paper analyses the problem of aggregating judgments over multiple interconnected issues. Voters share a common preference for reaching true collective judgments, but hold private information about what the truth might be. Information conflicts may occur both between and within voters. Following Bozbay, Dietrich and Peters (2014), we assume strategic voting in a Bayesian voting game setting...

The paper proposes a two-phase methodology to support groups in multicriteria classification problems. The first phase, which relies on dominance-based rough set approach, takes as input a set of assignment examples, and generates as output a set of collective decision rules representing a generalized description of the preference information of the decision makers. The second phase then applie...