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Network centrality reflects node importance in networks, which is a challenging problem in social network analysis. Based on Fuzzy Set and MYCIN theory, this paper proposes a novel node centrality measuring method and models n-monkeys dataset, where n is 20. Initially, we created monkeys relationship graph and generated relationship matrix based on the monkeys' encountering times in a specific time...
In this work, we report an ongoing study that aims to apply cluster validation measures for analyzing email communications at an organizational level of a company. This analysis can be used to evaluate the company structure and to produce further recommendations for structural improvements. Our initial evaluations, based on data in the forms of emails logs and organizational structure for a large...
Social interactions, when analyzed, can provide several information to help intuitive understanding of individuals and their interactions. Social Network Analysis (SNA) is a study field that investigates people's interaction patterns. These patterns, when mapped, enable a detailed and in-depth view of individuals' groups. In the context of distance learning, this paper presents an analysis that uses...
Recommender systems (RS) performance largely depends on diverse types of input that characterize users' preference in the form of both explicit and implicit feedbacks. An explicit feedback is stated directly by an explicit input from users regarding their interest in some options of services or products. Such feedback, however, is not always available. On the other hand, an implicit feedback, which...
We investigate a formal characterisation of interactional justice asa mechanism for self-organisation of institutional rules in an open system, in order to address issues of congruence, acceptability and risk. The process of interactional justice uses opinion formation over a social network with respect to a shared set of congruent values, to transform a set of individual, subjective self-assessments...
The ability to discover patterns of interest in criminal networks can support and ease the investigation tasks by security and law enforcement agencies. By considering criminal networks as a special case of social networks, we can properly reuse most of the state-of-the-art techniques to discover patterns of interests, i.e., hidden and potential links. Nevertheless, in time-sensible scenarios, like...
Recent years have seen robust advancements in robotic platforms for multiple users, while HRI research is increasingly examining small group interactions. However, there has been little consideration of appropriate methodologies for design or development of human-robot interactions to foster and enhance context-specific shared goals, interactions, and experiences within larger communities. This paper...
Key resources are important, influential and powerful performers in a social network structure. Identifying them in the social network of a business process activity is beneficial and rewarding. One of the most effective centrality measures for identification of the key nodes in a social network is to rank resources based on a selection of criteria. PageRank is a representative example of such algorithms,...
When two nodes in an opportunistic network meet, a utility function is generally employed to select the data that have to be exchanged between them, in order to maximize the chance of message delivery and to minimize congestion. The utility function computes weighted sums of various parameters, such as node centrality, similarity, trust, etc. Most of the existing solutions pre-compute the weights...
The Department of Defense (DoD) manages a large, complex system of systems that must operate together on the battlefield to deliver value. However, it is difficult to understand the network wide impacts of changes to the system of systems. The DoD has had difficulty managing this system of systems due to the scale and complexity of the network and traditional systems engineering tools do not provide...
Consider a data source comprised of a graph with marks on its edges and vertices. Examples of such data sources are social networks, biological data, web graphs, etc. Our goal is to design schemes that can efficiently compress and store such data. We aim for universal compression, i.e. without making assumptions about the stochastic properties of the data. To make sense of this, we employ the framework...
In this work, we study the information spreading time in multiplex networks, adopting the gossip (random-walk) based information spreading model. A new metric called multiplex conductance is defined based on the multiplex network structure and used to quantify the information spreading time in a general multiplex network in the idealized setting. Multiplex conductance is then evaluated for some interesting...
In September 2016, a fire in one of Puerto Rico's ten major power stations left over 1.5 million people without power and blacked out a significant portion of the island. This massive failure of the power system of systems is an example of how systems engineers require better methods for understanding complex, networked systems of systems. This paper proposes adapting social network analysis tools...
Graph sampling techniques via random walk crawling have been popular for analyzing statistical characteristics of large online social networks due to simple implementation and provable guarantees on unbiased estimates. Despite the growing popularity, the ‘cost’ of sampling and its true impact on the accuracy of estimates still have not been carefully studied. In addition, the random walk-based methods...
The task of identifying influential spreaders for various big data social network applications plays a crucial role in social networks, and lays the foundation for predictive or recommended applications. Though there are several kinds of methods for this task, most of these methods exploit global computing, and are time-consuming for large-scale social networks. In this paper, by combining the degree...
The pervasiveness of smartphones equipped with various built-in sensors combined with the capability of serving multiple applications that could access social network information introduces next generation soft biometrics tools that could be used to verify a user's identity through their social behavior. Smart mobile devices can provide multi-modal data acquisition from various social networking applications,...
Some recent research projects, inspired by the widespread availability of sensor-provided smartphones, have built harvesting experiments to collect large quantities of data in urban areas. These efforts produced new real-world datasets, typically focusing on different technological aspects (GPS and Bluetooth mobility traces or WiFi indicators) and, more recently, also on user-related data, from low-level...
In this paper, we propose a new version of the LBRW (Learning based Random Walk), LBRW-Co, for predicting users co-occurrence based on mobility homophily and social links. More precisely, we analyze and mine jointly spatio-temporal and social features with the aim to predict and rank users co-occurrences. Experiments are performed on the Foursquare LBSN with accurate and refined measurements. Experimental...
The academic mobility is one of key factors that enable the globalization of research and education. In this paper we study the network of ERASMUS staff and student exchange agreements between academic institutions involved in FETCH - a big European project oriented towards future education and training in computer science. The structure of the network was investigated relying on standard metrics...
The Service Oriented Computing (SOC) paradigm promotes building new applications by discovering and then invoking services, i.e., software components accessible through the Internet. Discovering services means inspecting registries where textual descriptions of services functional capabilities are stored. To automate this, existing approaches index descriptions and associate users' queries to relevant...
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