On the prevalence of hierarchies in social networks

In this paper, we introduce two novel evolutionary processes for hierarchical networks referred to as dominance- and prestige-based evolution models, i.e., DBEM and PBEM, respectively. Our models are deterministic in nature which allows for closed-form derivation of equilibrium points for such type of networks, for the special case of complete networks. After deriving these equilibrium points, we are somewhat surprised in recovering the exponential and power-law strength distribution as the shared property of the resulting hierarchal networks. Additionally, we compute the network properties, Geodesic distance distribution and centrality closeness, for each model in closed form. Interestingly, these results demonstrate very different roles of hubs for each model, shedding the light on the evolutionary advantages of hierarchies in social networks: in short, hierarchies can lead to efficient sharing of resources and robustness to random failures. For the general case of any hierarchical network, we compare the estimations of tie intensities and node strengths using the proposed models to open-source real-world data. The prediction results are statistically compared using the Kolmogorov–Smirnov test with the original data

Accuracy of affiliation information in Microsoft Academic: Implications for institutional level research evaluation

In this work, we study the accuracy of affiliation information in Microsoft Academic (MA). To conduct this study, we have considered the full set of publications assigned to Leiden University (LU) as provided by two different data sources: MA and Web of Science (WoS). The results of this study suggest that a considerable number of publications in MA have missing or wrong affiliation information

A Baseline Method for Genealogical Entity Resolution

In this paper we study the application of entity resolution (ER) techniques on a real-world multi-source genealogical dataset. Our goal is to identify all persons involved in various notary acts and link them to their birth, marriage and death certificates. In order to evaluate the performance of a baseline approach based on existing techniques, an interactive interface is developed for getting feedback from human experts in the field of genealogy. We perform an empirical evaluation in terms of precision, recall and F-score. We show that the baseline approach is not sufficient for our purposes and discuss future improvements

Investigation of a baseline method for genealogical entity resolution

In this paper we study the application of entity resolution (ER) techniques on a real-world multi-source genealogical dataset. Our goal is to identify all persons involved in various notary acts and link them to their birth, marriage and death certificates. In order to evaluate the performance of a baseline approach based on existing techniques, an interactive interface is developed for getting feedback from human experts in the field of genealogy. We perform an empirical evaluation in terms of precision, recall and F-score. We show that the baseline approach is not sufficient for our purposes and discuss future improvements

An interactive, web-based tool for genealogical entity resolution

We demonstrate an interactive, web-based tool which helps historians to do Genealogical Entitiy Resolution. This work has two main goals. First, it uses Machine Learning (ML) algorithms to assist humanites researchers to perform Genealogical Entity Resolution. Second, it facilitates the generation of benchmark data for computer scientists to improve available ML-based Entity Resolution techniques

An Interactive,Web-based Tool for Genealogical Entity Resolution (demonstration)

We demonstrate an interactive, web-based tool which helps historians to do Genealogical Entity Resolution. This work has two main goals: First, it uses Machine Learning (ML) algorithms to assist humanities researchers to perform Genealogical Entity Resolution. Second, it facilitates the generation of benchmark data for computer scientists to improve available ML-based Entity Resolution techniques

Advancing Evolutionary Coordination for Fixed-Wing Communications UAVs

In this paper we present advances to our previously proposed coordination system for groups of unmanned aerial vehicles that provide a network backbone over mobile ground-based vehicles. Evolutionary algorithms are employed in order to evolve flying manoeuvres that position the aerial vehicles. The updates to the system include obstacle representation, a packing mechanism to permit efficient dynamic allocation of ground-based vehicles to their supporting aerial vehicles within large-scale environments, and changes to time synchronisation. The experimental results presented in this paper show that the system is able to adaptively form sparse formations that cover as many ground-based vehicles as possible, optimising the use of the available power

Toward Soft Heterogeneity in Robotic Swarms (demonstration)

Diversity and inequality are essences of our real world. Ant colonies are comprised of hundreds of individuals, with no two of them being exactly identical. A flock of birds contains individuals with slight variations in size, speed and vision. Looking at human societies such diversity can be seen among individuals differing in body shape and in physical and cognitive abilities. The concept of softly heterogeneous robotic swarms uses the notion of heterogeneity in nature, and introduces a swarm of robots which all have the same goals, but have minor differences in their capabilities. This term is in contrast to the hard heterogeneity of swarms in which robots are of strictly different types and have strictly different goals and capabilities