14 Result(s)
within
English
Luca Rossi
Chapter
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Chapter and Conference Paper
Approximate Axial Symmetries from Continuous Time Quantum Walks
The analysis of complex networks is usually based on key properties such as small-worldness and vertex degree distribution. The presence of symmetric motifs on the other hand has been related to redundancy and...
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Chapter and Conference Paper
Information Theoretic Prototype Selection for Unattributed Graphs
In this paper we propose a prototype size selection method for a set of sample graphs. Our first contribution is to show how approximate set coding can be extended from the vector to graph domain. With this fr...
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Chapter and Conference Paper
Uniform Access to Non-relational Database Systems: The SOS Platform
Non-relational databases (often termed as NoSQL) have recently emerged and have generated both interest and criticism. Interest because they address requirements that are very important in large-scale applicat...
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Chapter and Conference Paper
Transitive State Alignment for the Quantum Jensen-Shannon Kernel
Kernel methods provide a convenient way to apply a wide range of learning techniques to complex and structured data by shifting the representational problem from one of finding an embedding of the data to that...
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Chapter and Conference Paper
Node Centrality for Continuous-Time Quantum Walks
The study of complex networks has recently attracted increasing interest because of the large variety of systems that can be modeled using graphs. A fundamental operation in the analysis of complex networks is...
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Chapter and Conference Paper
Attributed Graph Kernels Using the Jensen-Tsallis q-Differences
We propose a family of attributed graph kernels based on mutual information measures, i.e., the Jensen-Tsallis (JT) q-differences (for q ∈ [1,2]) between probability distributions over the graphs. To this end, we...
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Chapter and Conference Paper
An Edge-Based Matching Kernel Through Discrete-Time Quantum Walks
In this paper, we propose a new edge-based matching kernel for graphs by using discrete-time quantum walks. To this end, we commence by transforming a graph into a directed line graph. The reasons of using the...
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Chapter and Conference Paper
The Average Mixing Matrix Signature
Laplacian-based descriptors, such as the Heat Kernel Signature and the Wave Kernel Signature, allow one to embed the vertices of a graph onto a vectorial space, and have been successfully used to find the opti...
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Chapter and Conference Paper
Edge Centrality via the Holevo Quantity
In the study of complex networks, vertex centrality measures are used to identify the most important vertices within a graph. A related problem is that of measuring the centrality of an edge. In this paper, we...
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Chapter
DATA, DATA, AND MORE DATA
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Chapter
DATA MODEL INTEGRATION: THE GLOBAL EPIDEMIC AND MOBILITY FRAMEWORK
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Chapter
Migrant Digital Space: Building an Incomplete Map to Navigate Public Online Migration
This chapter introduces the concept of migrant digital space (MDS). MDS is defined as configured by migrants’ online activity before the journey, en route, and when settling down, and as a space shaped by prac...
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Chapter
Caring for (Big) Data: An Introduction to Research Methodologies and Ethical Challenges in Digital Migration Studies
Digital technologies present new methodological and ethical challenges for migration studies: from ensuring data access in ethically viable ways to privacy protection, ensuring autonomy, and security of resear...
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Chapter
Contrapuntal Connectedness: Analysing Relations Between Social Media Data and Ethnography in Digital Migration Studies
This chapter presents a rethinking of the relationship between ethnography and so-called big social data as being comparable to those between a sum and its parts (Strathern 1991/2004). Taking cue from Tim Ingo...
