Centrality in heterogeneous social networks for lurkers detection: An approach based on hypergraphs

Nowadays, social networks provide users an interactive platform to create and share heterogeneous content for a lot of different purposes (eg, to comment events and facts, and express and share personal opinions on specific topics), allowing millions of individuals to create online profiles and share personal information with vast networks known and sometimes also unknown people. Knowledge about users, content, and relationships in a social network may be used for an adversary attack of some victims easily. Although a number of works have been done for data privacy preservation on relational data, they cannot be applied in social networks and in general for big data analytics. In this paper, we first propose a novel data model that integrates and combines information on users belonging to 1 or more heterogeneous online social networks, together with the content that is generated, shared, and used within the related environments, using an hypergraph data structure; then we implemented the most diffused centrality measures and also introduced a new centrality measurebased on the concept of neighborhood among usersthat may be efficiently applied for a number of data privacy issues, such as lurkers and neighborhood attack prevention, especially in interest-based social networks. Some experiments using the Yelp dataset are discussed

Nearest query on distributed binary trees starting from a random node

This paper proposes a new distributed data structure based on binary trees to support k-nearest neighbor queries over very large databases. The indexing structure is distributed across a network of “peers”, where each one hosts a part of the tree and communication among nodes is realized by message passing. The advantages of this kind of approach are mainly two: it is possible to (i) handle a larger number of nodes and points than a single peer based architecture and (ii) to manage in an efficient way computation of multiple queries. In particular, we propose a novel version of the k-nearest neighbor algorithm that is able to start the query in a randomly chosen peer. Preliminary experiments have demonstrated that in about 65% of cases a query, which starts in random node, does not involve the peer containing the root of the tre

Influence Analysis in Online Social Networks Using Hypergraphs

In this paper, we describe a novel data model for online social networks based on hypergraphs. We show how an influence analysis problem can be properly faced leveraging the introduced network structure. In particular, we implemented a bio-inspired maximization algorithm on the top of the hypergraph model, exploiting the concept of influential path. Preliminary experiments using data of several social networks show how our approach obtains very promising results and encourage the research in this direction

Sentiment analysis on yelp social network

In this paper, we propose a novel data model for Multimedia Social Networks, i.e. particular social media networks that combine information on users belonging to one or more social communities together with the content that is generated and used within the related environments. The proposed model relies on the hypergraph data structure to capture and represent in a simple way all the different kinds of relationships that are typical of social media networks, and in particular among users and multimedia content. We also introduce some user and multimedia ranking functions to enable different applications. Finally, some experiments concerning effectiveness of the approach for supporting relevant information retrieval activities are reported and discussed

A novel approach to query expansion based on semantic similarity measures

In this paper, we present a framework supporting information retrieval over corpora of documents using an automatic sematic query expansion approach. The main idea is to expand the set of words used as query terms exploiting the notion of semantic similarity between the concepts related to the search terms. We leverage existing lexical resources and similarity metrics computed among terms to generate - by a proper mapping into a vectorial space - an index for the fast retrieval of a set of terms "semantically correlated" to a given query term. The vector of expanded terms is then exploited in the query stage to retrieve documents that are significantly related to specific combinations of the query terms. Preliminary experimental results concerning efficiency and effectiveness of the proposed approach are reported and discussed

Progress in pediatrics in 2013: Choices in allergology, endocrinology, gastroenterology, hypertension, infectious diseases, neonatology, neurology, nutrition and respiratory tract illnesses

This review will provide new information related to pathophysiology and management of specific diseases that have been addressed by selected articles published in the Italian Journal of Pediatrics in 2013, focusing on allergology, endocrinology, gastroenterology, hypertension, infectious diseases, neonatology, neurology, nutrition and respiratory tract illnesses in children. Recommendations for interpretation of skin prick test to foods in atopic eczema, management of allergic conjunctivitis, hypertension and breastfeeding in women treated with antiepileptic drugs and healthy breakfast have been reported. Epidemiological studies have given emphasis to high incidence of autoimmune disorders in patients with Turner syndrome, increasing prevalence of celiac disease, frequency of hypertension in adolescents, incidence and risk factor for retinopathy of prematurity. Advances in prevention include elucidation of the role of probiotics in reducing occurrence of allergies and feeding intolerance, and events of foetal life that influence later onset of diseases. Mechanistic studies suggested a role for vitamin D deficiency in asthma and type 1 diabetes and for reactivation of Varicella-Zoster virus in aseptic meningitis. Regarding diagnosis, a new mean for the diagnosis of hyperbilirubinaemia in newborns, a score for recognition of impaired nutritional status and growth and criteria for early Dyke-Davidoff-Masson Syndrome have been suggested. New therapeutic approaches consist of use of etanercept for reducing insulin dose in type 1 diabetes, probiotics in atopic eczema, and melatonin in viral infections

Data-driven Network Orchestrator for 5G Satellite-Terrestrial Integrated Networks: The ANChOR Project

Satellite communications (SatCom) have a role of advanced service enablers in the new virtual networks, following 3GPP specifications. Specifically, the satellite peculiar charac- teristics are of paramount importance to dynamically activate capabilities, such as multicast and broadcast channels, sudden traffic offloading, capacity bonding, and cost-efficient coverage of uncovered areas. A key aspect to achieve a seamless and efficient integration be- tween satellite and terrestrial infrastructures is to make satellite resource management dynamic and with a centralised control of a single orchestrator that has visibility of the end-to-end network. Considering the adoption of Software Defined Networking (SDN) and Network Function Virtualization (NFV) paradigms and the upcoming 5th generation of mobile communications (5G), this paper presents the ongoing work within the European Space Agency (ESA) ANChOR project, whose main output will be a data-driven Network Controller and Orchestrator for SatCom networks. This tool will be based on Artificial Intelligence (AI) / Machine Learning (ML)-based techniques to properly allocate resources exploiting some feedback knowledge of the network and it aims to support different services over 5G integrated satellite- terrestrial networks