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Due to the increasing popularity of cooking-recipe sharing sites and the success of complex network science, attention has recently been devoted to developing an effective networkbased method of analyzing the characteristics of ingredient combinations used in recipes. Unlike previous approaches dealing with static properties, we aim at analyzing the dynamical changes in ingredient pairs jointly used...
Social networks (SNs) have become essential communication tools in recent years, generating a large amount of information about its users that can be analysed with data processing algorithms. Recently, a new type of SN user has emerged: jihadists that use SNs as a tool to recruit new militants and share their propaganda. In this paper, we study a set of indicators to assess the risk of radicalisation...
Natural disasters frequently occur all over the world in recent years, and the disaster research is called for concern. The current research shows that a disaster often causes different kinds of other secondary disasters, therefore the related aspects about disaster chain is needed to be intensively investigate. This paper firstly introduces the state of art of disaster chain and then adapts the complex...
Big Data Analysis (BDA) has attracted considerable interest and curiosity from scientists of various fields recently. As big size and complexity of big data, it is pivotal to uncover hidden patterns, bursts of activity, correlations and laws of it. Complex network analysis could be effective method for this purpose, because of its powerful data organization and visualization ability. Besides the general...
The explosion by amount of codes as well as the swelling logic complexity have stifled the performance of the traditional fault-location methods since the resource adopted during this process is unacceptable. Under such a situation, a scheme to locate the faults in complex software more effectively has been proposed in this paper based on networks community theory. First, on the base of establishing...
The act of learning is becoming more and more sophisticated, thanks to several models and tools available today, like MOOCs, personalization, social networks, Web 2.0, gamification and others. This vast landscape leads to a huge amount of datasets thus the Big Data paradigm is also being adopted. Joined with Big Data is the emergency of extracting information about students' learning interactions...
In this paper, we describe a case study in a large metropolis in which, based on data collected by digital sensors, we sought to understand mobility patterns of people using buses and how this can generate knowledge to suggest interventions to be applied incrementally to the transportation network in use. We first estimated an Origin-Destination matrix of bus users based on datasets about ticket validation...
The study of world city networks becomes one of the hottest research areas. Mining the important nodes has been important research questions in network evaluation of world city applications. In this paper, we firstly summarized the characteristics of world city network and evaluated their centrality and power of control. Then, the node importance evaluation methods based on network topologies were...
In this paper, we propose a method for extracting the backbone links and the weakness nodes via community detection algorithm in complex networks. Firstly, we use the community detection algorithm to divide the complex network, Secondly, By the original graph structure and the communities, we find the backbone links and the weakness nodes. Finally, we do experiment to prove the method is feasible...
Various network relationships in many complex social systems can be described effectively by multilayer networks, but we find that there are interactions between individuals attributes and their social relationships by a principle of homophily, which hence impact the process of information spread and social influence in complex social systems. In order to integrate individuals relationships and attributes...
Overlapping communities are pervasive in real-world networks. Therefore overlapping community detection is an important task for mining the structure and function of complex networks. Recently, many overlapping detection methods are proposed. Though achieving different goals, how to improve the performances of the community detection algorithms is still an open problem. In this paper, we propose a...
Many universities are working to improve their graduation rates. The factors that correlate to student success and hence graduation rates are many, varying from pre-institutional factors, including high school GPA and admissions scores, to institutional factors, including student support services and the quality of faculty. An essential institutional factor that is often overlooked is the structure...
In a world full of connections between people and objects, new needs arise requiring multidisciplinary analysis of these new networks. This work presents a approach to analyze an Internet Service Provider (ISP) database using a minimal cover of implications extracted from formal concept analysis and complex network techniques. Our goal is to analyze access to the 25 most visited websites to find access...
The network of credit reference is a typical complex network in the theoretical level and practical level. In the big data era, in order to break the privacy of the credit calculation method and promote its development, this paper proposes a big data mining algorithm on the network of credit reference, which modifies the algorithm of traditional machine learning algorithm and the algorithm of HMM...
In a scientific research network, to determine the influence of an academic research, a key is to build and evaluate properties of its cited references or co-author networks. To analyze 18,000 lines of original data from Problem C given in 2014 MCM/ICM (Mathematical Contest In Modeling /Interdisciplinary Contest In Modeling), the Pajek software was used with obtaining a result that correlations among...
How the hotspot or congestion area evolves in a large scale complex networks is still not clear. The prediction of such behavior is more difficult. In this paper, the classical Fast-Newman algorithms for community detection is improved by considering node weight and edge weight in the network model. The evolution of the communities are reconstructed from the network trace. The relation between the...
Complex networks of direct relevance to biomedicine have not yet been fully mapped largely due to the incompleteness, isolation, and heterogeneity of data. The Semantic Web, by providing a technical framework for the integration and sharing of heterogeneous databases in different domains, can potentially enable more effective complex network mapping and analysis. However, the feasibility of using...
Currently, the methods of entity relationship modeling are mainly based on existing historical data or Complex Networks, because one-dimensional elements characterizing clusters relationship can't be a true reflection of the entity relationship and potential structure of IOT(Internet of Things). This paper proposes a method of entity relationship modeling of IOT based on Supernetwork, by considering...
This paper presents results of the analysis of a tourism information web-site (AmFostAcolo.ro) by using Complex Networks (CN) methods. The work accomplished here complements a previous paper, where we discussed data extraction and modelling into a complex network. Properties of the resulted network, communities and vertices are looked upon, in order to extract useful information and detect social...
It is a common problem that cost of extracting data for network analysis could be very high. Also sometimes in the Internet is it hard to find graph with desired features such as node degree or clustering level. Because of that graph generators can than be very helpful. In the past bunch of models of such generators was developed: random graphs, small worlds and scale free networks. All of these generators...
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