FROM SMALL-WORLDS TO BIG DATA:TEMPORAL AND MULTIDIMENSIONAL ASPECTS OF HUMAN NETWORKS

In this thesis we address the close interplay among mobility, offline relationships and online interactions and the related human networks at different dimensional scales and temporal granularities. By generally adopting a data-driven approach, we move from small datasets about physical interactions mediated by human-carried devices, describing small social realities, to large-scale graphs that evolve over time, as well as from human mobility trajectories to face-to-face contacts occurring in different geographical contexts. We explore in depth the relation between human mobility and the social structure induced by the overlapping of different people's trajectories on GPS traces collected in urban and metropolitan areas. We define the notions of geo-location and geo-community which are operational in describing in a unique framework both spatial and social aspects of human behavior. Through the concept of geo-community we model the human mobility adopting a bipartite graph. Thanks to this graph representation we can generate a social structure that is plausible w.r.t. the real interactions. In general the modeling approach have the merit for reporting the mobility in a graph-theoretic framework making the study of the interplay mobility/sociality more affordable and intuitive. Our modeling approach also results in a mobility model, Geo-CoMM, which lies on and exploits the idea of geo-community. The model represents a particular instance of a general framework we provide. A framework where the social structure behind the preferred-location based mobility models emerges. We validate Geo-CoMM on spatial, temporal, pairwise connectivity and social features showing that it reproduces the main statistical properties observed in real traces. As concerns the offline/online interplay we provide a complete overview of the close connection between online and offline sociality. To reach our goal we gather data about offline contacts and social interactions on Facebook of a group of students and we propose a multidimensional network analysis which allows us to deeply understand how the characteristics of users in the distinct networks impact each other. Results show how offline and Facebook friends are different. This way we confirm and worsen the general intuition that online social networks have shifted away from their original goal to mirror the offline sociality of individuals. As for the role and the social importance, it becomes apparent that social features such as user popularity or community structure do not transfer along social dimensions, as confirmed by our correlation analysis of the network layers and by the comparison among the communities. In the last chapters we analyze the evolution of the online social network from a physical time perspective, i.e. considering the graph evolution as a graph time-series and not as a function of the network basic properties (number of nodes or links). As for the physical time in a user-centric viewpoint, we investigate the bursty nature of the link creation process in online social network. We prove not only that it is a highly inhomogeneous process, but also identify patterns of burstiness common to all nodes. Then we focus on the dynamic formation of two fundamental network building components: dyads and triads. We propose two new metrics to aid the temporal analysis on physical time: link creation delay and triangle closure delay. These two metrics enable us to study the dynamic creation of dyads and triads, and to highlight network behavior that would otherwise remain hidden. In our analysis, we find that link delays are generally very low in absolute time and are largely independent of the dates people join the network. To highlight the social nature of this metric, we introduce the term \textit{peerness} to quantify how well linked users overlap in lifetimes. As for triadic closure delay we first introduce an algorithm to extract of temporal triangle which enables us to monitor the triangle formation process, and to detect sudden changes in the triangle formation behavior, possibly related to external events. In particular, we show that the introduction of new service functionalities had a disruptive impact on the triangle creation process in the network

Micro-intelligence for the IoT: logic-based models and technologies

Computing is moving towards pervasive, ubiquitous environments in which devices, software agents and services are all expected to seamlessly integrate and cooperate in support of human objectives. An important next step for pervasive computing is the integration of intelligent agents that employ knowledge and reasoning to understand the local context and share this information in support of intelligent applications and interfaces. Such scenarios, characterised by "computation everywhere around us", require on the one hand software components with intelligent behaviour in terms of objectives and context, and on the other their integration so as to produce social intelligence. Logic Programming (LP) has been recognised as a natural paradigm for addressing the needs of distributed intelligence. Yet, the development of novel architectures, in particular in the context Internet of Things (IoT), and the emergence of new domains and potential applications, are creating new research opportunities where LP could be exploited, when suitably coupled with agent technologies and methods so that it can fully develop its potential in the new context. In particular, the LP and its extensions can act as micro-intelligence sources for the IoT world, both at the individual and the social level, provided that they are reconsidered in a renewed architectural vision. Such micro-intelligence sources could deal with the local knowledge of the devices taking into account the domain specificity of each environment. The goal of this thesis is to re-contextualise LP and its extensions in these new domains as a source of micro-intelligence for the IoT world, envisioning a large number of small computational units distributed and situated in the environment, thus promoting the local exploitation of symbolic languages with inference capabilities. The topic is explored in depth and the effectiveness of novel LP models and architectures -and of the corresponding technology- expressing the concept of micro-intelligence is tested

Recent advances in petri nets and concurrency

CEUR Workshop Proceeding

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications

Advances in knowledge discovery and data mining Part II

19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II</p

The Essence of Software Engineering

Software Engineering; Software Development; Software Processes; Software Architectures; Software Managemen

Dwelling on ontology - semantic reasoning over topographic maps

The thesis builds upon the hypothesis that the spatial arrangement of topographic features, such as buildings, roads and other land cover parcels, indicates how land is used. The aim is to make this kind of high-level semantic information explicit within topographic data. There is an increasing need to share and use data for a wider range of purposes, and to make data more definitive, intelligent and accessible. Unfortunately, we still encounter a gap between low-level data representations and high-level concepts that typify human qualitative spatial reasoning. The thesis adopts an ontological approach to bridge this gap and to derive functional information by using standard reasoning mechanisms offered by logic-based knowledge representation formalisms. It formulates a framework for the processes involved in interpreting land use information from topographic maps. Land use is a high-level abstract concept, but it is also an observable fact intimately tied to geography. By decomposing this relationship, the thesis correlates a one-to-one mapping between high-level conceptualisations established from human knowledge and real world entities represented in the data. Based on a middle-out approach, it develops a conceptual model that incrementally links different levels of detail, and thereby derives coarser, more meaningful descriptions from more detailed ones. The thesis verifies its proposed ideas by implementing an ontology describing the land use ‘residential area’ in the ontology editor Protégé. By asserting knowledge about high-level concepts such as types of dwellings, urban blocks and residential districts as well as individuals that link directly to topographic features stored in the database, the reasoner successfully infers instances of the defined classes. Despite current technological limitations, ontologies are a promising way forward in the manner we handle and integrate geographic data, especially with respect to how humans conceptualise geographic space

Choreographing the extended agent : performance graphics for dance theater

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2005.Includes bibliographical references (v. 2, leaves 448-458).The marriage of dance and interactive image has been a persistent dream over the past decades, but reality has fallen far short of potential for both technical and conceptual reasons. This thesis proposes a new approach to the problem and lays out the theoretical, technical and aesthetic framework for the innovative art form of digitally augmented human movement. I will use as example works a series of installations, digital projections and compositions each of which contains a choreographic component - either through collaboration with a choreographer directly or by the creation of artworks that automatically organize and understand purely virtual movement. These works lead up to two unprecedented collaborations with two of the greatest choreographers working today; new pieces that combine dance and interactive projected light using real-time motion capture live on stage. The existing field of"dance technology" is one with many problems. This is a domain with many practitioners, few techniques and almost no theory; a field that is generating "experimental" productions with every passing week, has literally hundreds of citable pieces and no canonical works; a field that is oddly disconnected from modern dance's history, pulled between the practical realities of the body and those of computer art, and has no influence on the prevailing digital art paradigms that it consumes.(cont.) This thesis will seek to address each of these problems: by providing techniques and a basis for "practical theory"; by building artworks with resources and people that have never previously been brought together, in theaters and in front of audiences previously inaccessible to the field; and by proving through demonstration that a profitable and important dialogue between digital art and the pioneers of modern dance can in fact occur. The methodological perspective of this thesis is that of biologically inspired, agent-based artificial intelligence, taken to a high degree of technical depth. The representations, algorithms and techniques behind such agent architectures are extended and pushed into new territory for both interactive art and artificial intelligence. In particular, this thesis ill focus on the control structures and the rendering of the extended agents' bodies, the tools for creating complex agent-based artworks in intense collaborative situations, and the creation of agent structures that can span live image and interactive sound production. Each of these parts becomes an element of what it means to "choreograph" an extended agent for live performance.Marc Downie.Ph.D