1,721,832 research outputs found
Introduction to ontology engineering
No full textThis chapter provides an introduction to ontology engineering discussing the role of ontologies in informative systems, presenting a methodology for ontology design, and introducing ontology languages. The chapter starts by explaining why ontologies are needed in informative systems, then it introduces the reader to ontologies by leading him/her in a stepwise guide to ontology design. It concludes by introducing ontology languages and standards. This is a primer reading aimed at preparing novice readers of this book to understanding more complex dissertations; for this reason it can be avoided by expert readers
A non-invasive method for the conformance assessment of pair programming practices based on hierarchical hidden Markov models
No full textWe specify a non-invasive method allowing to estimate the time each developer of a pair spends over the development activity, during Pair Programming. The method works by performing first a behavioural fingerprinting
of each developer – based on low level event logs – which then is used to operate a segmentation over the log sequence produced by the pair: in a timelined log event sequence this is equivalent to estimating the times of the switching between developers. We model the individual developer’s behaviour by means of a Markov Chain – inferred from the logs – and model the developers’ role-switching process by a further, higher level, Markov Chain. The overall model consisting in the two nested Markov Chains belongs to the class of Hierarchical Hidden Markov Models. The method
could be used not only to assess the degree of conformance with respect to predefined Pair Programming switch-times policies, but also to capture the characteristics of a given programmers pair’s switching process, namely in the context of Pair Programming effectiveness studies
Neighbor-avoiding random walks for information dissemination
No full textIn order to behave correctly, distributed consensus algorithms – which play a key role in several self-organized systems - require an efficient information dissemination mechanism. This is a non-trivial issue when agents communicate over an unstructured network, where each node has to rely only on local information to perform packet forwarding. Often this issue is approached by having the message to be disseminated by gossiping, i.e. by means of some kind of random walk. However, in many networks, topological bottlenecks can hinder information propagation from one network region to another, thus allowing distinct regions to settle on a consensus state on their own. In this work we study the performance of neighbor-avoiding random walks for information dissemination and show – using random 2D geometric networks as reference networks – that such walks have a higher probability of crossing topological bottlenecks and lower hitting time with respect to other random walk policies
Can a rock song have a jazz audience? : relationship between folksonomy and collaborative filtering in music recommender systems
No full textIn this paper we investigate the relationship between a
folksonomy-based music classification and a music classification based on collaborative filtering, i.e. on the users' listening behavior. We found a correlation between folksonomy-based songs clustering and clustering computed using methods based on the audience listening behaviour and, using a combination of the two approaches, we also computed the eclecticism level of a sample set of users, finding that eclecticism seems to be a characteristic which changes according to the genre of music most loved by a user
Fuzzy service selection in active networks
No full textThe object selection problem requires the evaluation of the fitness of a candidate server object to execute a certain task on the basis of the information about its functional and non-functional features. Active networks store such information in a Trader agent that can be browsed or queried by client objects. In this paper, a fuzzy data model is proposed as the basis of the design of a Trader system. Such a Trader is based on a fuzzy query algebra allowing for deriving operator definitions (and, therefore, query execution mechanisms) at run time, on the basis of user-selected semantics
Business intelligence meets big data : an overview on security and privacy
Full text linkToday big data are the target of many research activities focusing on big data management and analysis, definition of zero latency approaches to data analytics, and protection of big data security and privacy. In particular, security and privacy are two important, while contrasting, requirements. Big data security usually refers to the use of big data to implement solutions increasing security, reliability, and safety of a distributed system. Big data privacy, instead, focuses on the protection of big data from unauthorized use and unwanted inference. In this paper, we start from the manifesto on Business Intelligence Meets Big Data [8] and the notions of full data and zero-latency analysis to discuss new challenges in the context of big data security and privacy
Risk-aware collaborative processes
No full textThe design and deployment of inter-organizational collaborative business process need to take into account risks posed by the process actors’ dysfunctional behavior. Estimating such risks is of paramount importance at the operational and/or organizational level. This talk will present a general methodology for analyzing risks connected to dysfunctional behavior of business process partners, and design risk-aware deployment of security countermeasures
Process Mining in Big Data Scenario
No full textIn the last years the management and analysis of big data generated from information systems are becoming one of the most important topics in the Business Process Intelligence (BPI). In this field researchers show how Process Mining could become very helpful in bridging the gap between data and processes. The aim of this work is to present and discuss a brief review of the literature reporting most of the Process Mining chances that meet Big Data and the challenges carried out, showing the critical aspects and the advantages of different solutions
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