1,721,358 research outputs found
Social network analytics, data science ethics & privacy-preserving analytics
No full textGoals
Over the past decade there has been a growing public fascination with the complex "connectedness" of modern society. This connectedness is found in many contexts: in the rapid growth of the Internet and the Web, in the ease with which global communication now takes place, and in the ability of news and information as well as epidemics and financial crises to spread around the world with surprising speed and intensity. These are phenomena that involve networks and the aggregate behavior of groups of people; they are based on the links that connect us and the ways in which each of our decisions can have subtle consequences for the outcomes of everyone else.
This crash course is an introduction to the analysis of complex networks, made possible by the availability of big data, with a special focus on the social network and its structure and function. Drawing on ideas from computing and information science, complex systems, mathematic and statistical modelling, economics and sociology, this lecture sketchily describes the emerging field of study that is growing at the interface of all these areas, addressing fundamental questions about how the social, economic, and technological worlds are connected.
Syllabus
•Big graph data and social, information, biological and technological networks
•The architecture of complexity and how real networks differ from random networks: node degree and long tails, social distance and small worlds, clustering and triadic closure. Comparing real networks and random graphs. The main models of network science: small world and preferential attachment.
•Strong and weak ties, community structure and long-range bridges. Robustness of networks to failures and attacks. Cascades and spreading. Network models for diffusion and epidemics. The strength of weak ties for the diffusion of information. The strength of strong ties for the diffusion of innovation.
•Practical network analytics with Cytoscape and Gephi. Simulation of network processes with NetLogo.
Reference Textbooks
David Easley, Jon Kleinberg: Networks, Crowds, and Markets (2010)
http://www.cs.cornell.edu/home/kleinber/networks-book/
Albert-Laszlo Barabasi. Network Science (2016)
http://barabasi.com/book/network-science
Network Analytics Software
Visual Analytics: Cytoscape http://www.cytoscape.org/
Gephi http://gephi.github.io/
Network Simulation: NetLogo
https://ccl.northwestern.edu/netlogo/
Data science ethics & privacy-preserving analytics
Data science created unprecedented opportunities but also new risks. Data science techniques might expose sensitive traits of individuals and invade their privacy, this information could be used to discriminate people based on their presumed characteristics, or profiles. Sophisticated data driven machine learning algorithms yield classification and prediction models of behavioral traits of individuals, such as credit score, insurance risk, health status, personal preferences and orientations, on the basis of personal data disseminated in the digital environment by users, with or
sometimes without their awareness. Such automated decision-making systems are often "black boxes", mapping user's features into a class label or a ranking value without exposing the reasons .
This is worrying not only for the lack of transparency, which undermines the trust of stakeholders, but also for possible social biases and prejudices hidden in the training data and learned by the algorithms, which may bring to discriminatory decisions or unfair actions. Gartner says that, within 2018, half of business ethics violations will occur through improper use of Big Data analytics .
Often, the achievements of data science are the result of re-interpreting available data for analysis goals that differ from the original reasons motivating data collection. Examples include mobile phone call records, originally collected by telecom operators for billing and operations, used for accurate and timely demography and human mobility analysis at country orregional scale. This re-purposing of data clearly shows the importance of legal compliance and data ethics technologies and safeguards to protect privacy and anonymity, secure data, engage users, avoid discrimination and misuse, account for transparency and fair use - to the purpose of seizing the opportunities of data science while controlling the associated risks. This is the focus of my lecture.
Syllabus
• Fairness, Accountability, Confidentiality, Accuracy: the ethical challenges of data science • Privacy-preserving data mining • Privacy-by-design and data-driven risk assessment • Democratizing data science: centralised vs. user-centric analytics • Personal data analytics, collective awareness • Algorithmic bias and ethical challenges of machine learning • Discrimination-aware data minin
On logic programs that do not fail
No full textThis paper investigates the advantages of reasoning on logic programs and queries that have only successful derivations. We consider an extension of the logic programming paradigm that combines guarded clauses and delay declarations. The main contribution of this paper consists of some general conditions for a class of programs and queries which imply that successful derivations only are present. A few practical instances of the method are studied, and their applicability demonstrated. The general conditions are derived extending proof methods originally developed for Prolog's programs. From the point of view of parallelism, the method is able to reason about termination (with success) of pipeline parallel executions of programs. In particular, we show some examples of parallelization of terminating Prolog programs. Moreover, from the point of view of nondeterminism, don't care nondeterminism can be safely adopted for the class of programs that have only successfull derivations
Datalog with non deterministic choice computes NDB-PTIME
No full textAbstractThis paper addresses the issue of non-deterministic extensions of logic database languages. After providing a brief overview of the main proposals in the literature, we concentrate on the analysis of the dynamic choice construct from the point of view of the expressive power. We show how such construct is capable of expressing several interesting deterministic problems, such as computing the complement of a relation, and non-deterministic ones, such as computing an ordering of a relation. We then prove that Datalog augmented with the dynamic choice expresses exactly the non-deterministic time-polynomial queries. We thus obtain a complete characterization of the expressiveness of the dynamic choice, and conversely achieve a characterization of the class of non-deterministic time-polynomial queries (NDB-PTIME) by means of a simple, declarative, and efficiently implementable language
On logic programs that always succeed
No full textAbstractWe introduce a generalized definition of SLD-resolution admitting restrictions on atom and/or clause selectability. Instances of these restrictions include delay declarations, input-consuming unification and guarded clauses.In the context of such a generalization of SLD-resolution, we offer a theoretical framework to reason about programs and queries such that all derivations are successful. We provide a characterization of those programs and queries which allows to reuse existing methods from the literature on termination and verification of Prolog programs
Verification of Meta-interpreters
No full textA novel approach to the verification of meta-interpreters is
introduced. We apply
a general purpose verification method for logic programs,
proposed by the authors,
to the case study of the Vanilla and other logic meta-interpreters.
We extend the standard notion of declarative correctness,
and design a criterion for proving
correctness of meta-interpreters in a general sense, including
amalgamated and reflective meta-interpreters.
The contribution of this paper can be summarized as follows:
under certain
natural assumptions, all interesting verification
properties lift up from the
object program to the meta-program, including
partial correctness, termination,
absence of errors, call patterns persistence,
correct instances of queries,
computed instances of queries.
Interestingly, it is possible to
establish these results on the basis of purely
declarative reasoning, using the mentioned proof method.
We believe that the obtained results illustrate
the broad applicability of the adopted verification principles
Mobility, Data Mining and Privacy
No full textThe technologies of mobile communications and ubiquitous computing pervade our society, and wireless networks sense the movement of people and vehicles, generating large volumes of mobility data. This is a scenario of great opportunities and risks: on one side, mining this data can produce useful knowledge, supporting sustainable mobility and intelligent transportation systems; on the other side, individual privacy is at risk, as the mobility data contain sensitive personal information. A new multidisciplinary research area is emerging at this crossroads of mobility, data mining, and privacy.
This book assesses this research frontier from a computer science perspective, investigating the various scientific and technological issues, open problems, and roadmap. The editors manage a research project called GeoPKDD, Geographic Privacy-Aware Knowledge Discovery and Delivery, funded by the EU Commission and involving 40 researchers from 7 countries, and this book tightly integrates and relates their findings in 13 chapters covering all related subjects, including the concepts of movement data and knowledge discovery from movement data; privacy-aware geographic knowledge discovery; wireless network and next-generation mobile technologies; trajectory data models, systems and warehouses; privacy and security aspects of technologies and related regulations; querying, mining and reasoning on spatiotemporal data; and visual analytics methods for movement data.
This book will benefit researchers and practitioners in the related areas of computer science, geography, social science, statistics, law, telecommunications and transportation engineering
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