Giorgio Terracina

University of Calabria | Università della Calabria · Dipartimento di Matematica e Informatica

Stream Reasoning (SR) focuses on developing advanced approaches for applying inference to dynamic data streams; it has become increasingly relevant in various application scenarios such as IoT, Smart Cities, Emergency Management, and Healthcare, despite being a relatively new field of research. The current lack of standardized formalisms and benchm...

Detecting sets of relevant patterns from a given dataset is an important challenge in data mining. The relevance of a pattern, also called utility in the literature, is a subjective measure and can be actually assessed from very different points of view. Rule-based languages like Answer Set Programming (ASP) seem well suited for specifying user-pro...

Detecting sets of relevant patterns from a given dataset is an important challenge in data mining. The relevance of a pattern, also called utility in the literature, is a subjective measure and can be actually assessed from very different points of view. Rule-based languages like Answer Set Programming (ASP) seem well suited for specifying user-pro...

Information diffusion in social networks is a classic and, at the same time, very current problem. In fact, information diffusers are always looking for new techniques to disseminate information of their interest by creating backbones among them. In this paper, we focus on a specific, but very current and relevant, scenario regarding this way of pr...

Reddit is one of the few social networks that handles Not Safe For Work (NSFW) content in an explicit and well-structured way. Despite this, in the past literature on Reddit, there are very few researches concerning this topic. In particular, a study on the text of NSFW comments and posts published in this social medium is missing. In this paper, w...

The analysis of people's comments in social platforms is a widely investigated topic because comments are the place where people show their spontaneity most clearly. In this paper, we present a network-based data structure and a related approach to represent and manage the underlying semantics of a set of comments. Our approach is based on the extr...

The analysis of people’s comments in social platforms is a widely investigated topic because comments are the place where people show their spontaneity most clearly. In this article, we present a network-based data structure and a related approach to represent and manage the underlying semantics of a set of comments. Our approach is based on the ex...

Reddit is one of the few social networks that handles Not Safe For Work (NSFW) content in an explicit and well-structured way. Despite this, in the past literature on Reddit, there are very few researches concerning this topic. In particular, a study on the text of NSFW comments and posts published in this social medium is missing. In this paper, w...

Particulate matter with a diameter less than 2.5 micrometers (PM2.5) can be considered as the most dangerous air pollutant that affects human health. In addition, technological advances, such as those involving the Internet of Things (IoT) for monitoring air quality, have made it possible to monitor air quality for a lower cost. However, missing va...

The COVID-19 outbreak impacted almost all the aspects of ordinary life. In this context, social networks quickly started playing the role of a sounding board for the content produced by people. Studying how dramatic events affect the way people interact with each other and react to poorly known situations is recognized as a relevant research task....

In recent years, Reddit has attracted the interest of many researchers due to its popularity all over the world. In this paper, we aim at providing a contribution to the knowledge of this social network by investigating three of its aspects, interesting from the scientific viewpoint, and, at the same time, by analyzing a large number of application...

In the context of pattern mining, the utility of a pattern can be described as a preference ordering over a choice set; it can be actually assessed from very different perspectives and at different abstraction levels. However, while the topic of High-Utility Pattern Mining (HUPM) has been widely studied, the basic assumption is that each item in a...

In recent years, Reddit has attracted the interest of many researchers due to its popularity all over the world. In this article, we aim at providing a contribution to the knowledge of this social network by investigating three of its aspects, interesting from the scientific viewpoint, and, at the same time, by analysing a large number of applicati...

The investigation of anomalies is an important element in many scientific research fields. In recent years, this activity has been also extended to social networking and social internetworking, where different networks interact with each other. In these research fields, we have recently witnessed an important evolution because, beside networks of p...

The knowledge of interschema properties (e.g., synonymies, homonymies, hyponymies, sub-schema similarities) plays a key role for allowing decision making in sources characterized by disparate formats. In the past, a wide amount and variety of approaches to derive interschema properties from structured and semi-structured data have been proposed. Ho...

In the context of social networks, a renowned paper of New-man introduced the notion of "assortativity", also known as "assortative mixing". Strictly akin to the concept of homophily, it shows how much a node tends to associate with other nodes somewhat similar to it. Degree centrality is the most used similarity metrics for evaluating assortativ-i...

In the last few years, classical social networking is turning into the more complex social internetworking and is extending from human users to objects. Indeed, objects are becoming increasingly complex, smart and social so that several authors have recently started to investigate the Social Internet of Things (SIoT) and the Multiple IoT (MIoT) par...

The knowledge of interschema properties (e.g., synonymies, homonymies, hyponymies and subschema similarities) plays a key role for allowing decision-making in sources characterized by disparate formats. In the past, wide amount and variety of approaches to derive interschema properties from structured and semi-structured data have been proposed. Ho...

In the last few years, we have assisted in a great increase of the usage of strings in the most disparate areas. In the meantime, the development of the Internet has brought the necessity of managing strings from very different contexts and possibly using different alphabets. This issue is not addressed by the numerous string comparison metrics pre...

Betweenness centrality is one of the most known centrality measures in network analysis. It has been largely investigated in the past, and several extensions tailored to specific contexts, also involving IoT, have been proposed. However, the classical betweenness centrality is not able to correctly evaluate the centrality of nodes in a multiple IoT...

A Logic-Based Framework Leveraging Neural Networks for Studying the Evolution of Neurological Disorders - FRANCESCO CALIMERI, FRANCESCO CAUTERUCCIO, LUCA CINELLI, ALDO MARZULLO, CLAUDIO STAMILE, GIORGIO TERRACINA, FRANÇOISE DURAND-DUBIEF, DOMINIQUE SAPPEY-MARINIER

Smart cities, arising all around the globe, encourage the birth of new and different urban infrastructures, with interesting challenges and opportunities. Within each smart city, a smart community emerges, which integrates technological solutions for the definition of innovative models for the smart management of urban areas. In this paper, we desc...

Deductive formalisms have been strongly developed in recent years; among them, Answer Set Programming (ASP) gained some momentum, and has been lately fruitfully employed in many real-world scenarios. Nonetheless, in spite of a large number of success stories in relevant application areas, and even in industrial contexts, deductive reasoning cannot...

Prediction of disability progression in multiple sclerosis patients is a critical component of their management. In particular, one challenge is to identify and characterize a patient profile who may benefit of efficient treatments. However, it is not yet clear whether a particular relation exists between the brain structure and the disability stat...

In this paper, we investigate the scope of a thing in a multiple IoT scenario. First we introduce the concept of scope in general, and we illustrate how it has been investigated and applied in social networking. Then, we define the scope of a thing in a Multi-IoT scenario, modeled as an extension of a Social Internetworking System, and we propose a...

Recent advances in image acquisition and processing techniques, along with the success of novel deep learning architectures, have given the opportunity to develop innovative algorithms capable to provide a better characterization of neurological related diseases. In this work, we introduce a neural network based approach to classify Multiple Sclero...

In this paper, we propose a framework that aims at handling metrics among strings defined over heterogeneous alphabets. Furthermore, we illustrate in detail its application to generalize one of the most important string metrics, namely the edit distance. This last activity leads us to define the Multi-Parameterized Edit Distance (MPED). As for this...

Enhancing Datalog with existential quantification gives rise to Datalog∃, a powerful knowledge representation language widely used in ontology-based query answering. In this setting, a conjunctive query is evaluated over a Datalog∃ program consisting of extensional data paired with so-called “existential” rules. Owing to their high expressiveness,...

Sensor network analysis has become a challenging task. The detection of sensor anomalies is one of the most prominent topics in this research area. In the past, researchers mainly focused on the detection and analysis of single-sensor anomalies. In this paper, we shift the focus from a local approach, aimed to detect anomalies on single sensors, to...

Image recognition applications has been capturing interest of researchers for many years, as they found countless real-life applications. A significant role in the development of such systems has recently been played by evolutionary algorithms. Among those, HyperNEAT shows interesting results when dealing with potentially high-dimensional input spa...

In this paper, we present a new network-based approach to help experts investigate neurological disorders in which the connections among brain areas play a key role. Our approach receives the EEG of a patient and associates a network with it, with nodes that represent electrodes and with edges that denote the disconnection degree of the correspondi...

Heterogeneous wireless sensor networks are a source of large amount of different information representing environmental aspects such as light, temperature, and humidity. A very important research problem related to the analysis of the sensor data is the detection of relevant anomalies. In this work, we focus on the detection of unexpected sensor da...

This paper deals with the analysis of neurological disorders. In particular we focus on the potentialities of metadata to support the analysis process. We focus on the analysis of the Alzheimer disease and we show how computer-based analysis of metadata associated with clinical observations may help doctors in understanding clinical stages of a pat...

The incidence of neurological disorders is constantly growing, and the use of Artificial Intelligence techniques in supporting neurologists is steadily increasing. Deductive reasoning and neural networks are two prominent areas in AI that can support discovery processes; unfortunately, they have been considered as separate research areas for long t...

This paper presents a novel approach aiming at improving the White Matter (WM) fiber-bundle extraction approach described in (Stamile C et al Brain Informatics and Health: 8th International Conference, BIH, 2015). This provides anatomically coherent fiber-bundles, but it is unable to distinguish symmetric fiber-bundles. The new approach we are prop...

I NDIVIDUAL IDENTIFICATION OF SHARKS THROUGH DORSAL FIN: A NEW APPROACH THANKS TO ADVANCES IN COMPUTER SCI ENCE

Many difficult problems that are tractable when restricted to acyclic instances are good candidates to be solved efficiently whenever their structure is not precisely acyclic, but not far from that. This is the case for fundamental database problems such as answering conjunctive queries or counting the number of answers (without actually computing...

Synthesizing photo-realistic images is a challenging problem with many practical applications [15]. In many cases, the availability of a significant amount of images is crucial, yet obtaining them might be not trivial. For instance, obtaining huge databases of images is hard, in the biomedical domain, but strictly needed in order to improve both al...

In this paper, we propose an automated approach to extracting White Matter (WM) fiber-bundles through clustering and model characterization. The key novelties of our approach are: a new string-based formalism, allowing an alternative representation of WM fibers, a new string dissimilarity metric, a WM fiber clustering technique, and a new model-bas...

Information diffusion is a classical problem in social network analysis, which has been largely investigated with reference to single social networks. However, the current scenario is multi-social-network. Here, many social networks coexist and are strictly connected to each other, thanks to those users who join more social networks, acting as brid...

The construction of White Matter (WM) fiber-bundles has been largely investigated in the literature. Indeed, both manual and automatic approaches for isolating and extracting WM fiber-bundles have been proposed in the past. Each family of approaches has its pros and cons. One of the most known automatic approaches is QuickBundles (QB). Undoubtedly,...

In this paper we present a new model-guided approach to extracting anatomically plausible White Matter fiber-bundles from the high number of streamlines generated by tractography algorithms. Our approach is based on: (i) an approximate shape model of certain fiber-bundles constructed by an expert operator; (ii) a particular string representation of...

Consistent query answering over a database that violates primary key constraints is a classical hard problem in database research that has been traditionally dealt with logic programming. However, the applicability of existing logic-based solutions is restricted to data sets of moderate size. This paper presents a novel decomposition and pruning st...

In this paper we apply Answer Set Programming for analyzing properties of social networks, and we consider Information Diffusion in Social Network Analysis. This problem has been deeply investigated for single social networks, but we focus on a new setting where many social networks coexist and are strictly connected to each other, thanks to those...

This paper proposes a novel approach for monitoring heterogeneous wireless sensor networks and to identify hidden correlations between sensors. The technique is tested in an experimental environment based on the Building Management Framework. Results show that the proposed approach is actually capable of identifying hidden correlations, is robust t...

Information Diffusion is a classical problem in Social Network Analysis, where it has been deeply investigated for single social networks. In this paper, we begin to study it in a multi-social-network scenario, where many social networks coexist and are strictly connected to each other, thanks to those users who join more social networks. In this a...

Information Diffusion is a classical problem in Social Net-work Analysis, where it has been deeply investigated for single social networks. In this paper, we begin to study it in a multi-social-network scenario, where many social networks coexist and are strictly connected to each other, thanks to those users who join more social networks. In this...

Node Influence Maximization and Influential Node Charac-terization are classical problems in Social Network Analysis. Indeed, in the past, they have been deeply investigated with reference to single social networks. However, the current scenario is multi-social-network. Here, many social networks coexist and are strictly connected to each other, th...

In this paper we present a technique based on logic programming for data cleaning, and its application to a real use case from the Italian Healthcare System. The use case is part of a more complex project developing a business intelligence suite for the analysis of distributed archives of tumor-based diseases.

We report on preliminary research towards native algorithms for query answering over relational nonmonotonic multi-context systems (MCS), i.e., algorithms that do not rely on computing equilibria. Inspired by techniques for query answering in distributed answer set programming, we identify MCS settings where a generalized query answering algorithm...

Ontology-based reasoning is considered a crucial task in the area of knowledge management. In this context, the interest in approaches that resort to Datalog (and its extensions) for implementing various reasoning tasks over ontologies is growing. Nonetheless, looking from the developer point of view, one can notice that the editing environments fo...

Computing sequence similarity is a problem emerging in several areas of research. Current solution algorithms are often based on alignment methods under the assumption that matching symbols, or at least a substitution schema among them, are known in advance. This is natural for sequences defined over the same alphabet of symbols. However, for seque...

Datalog ∃ is the extension of Datalog allowing existentially quantified variables in rule heads. This language is highly expressive and enables easy and powerful knowledge-modelling, but the presence of existentially quantified variables makes reasoning over Datalog ∃ undecidable in the general case. Restricted classes of Datalog ∃ , such as shy, h...

In the area of data and knowledge management, ontology-based query answering (OB QA) is becoming more and more a relevant task [2,3]. In fact, many organizations and autonomous contributors are generating the so called "Web of Data", making publicly available Semantic Web repositories built either from scratch or by translation of existing data in...

Datalog ∃ is the extension of Datalog, allowing existen-tially quantified variables in rule heads. This language is highly expressive and enables easy and powerful knowledge-modeling, but the presence of existentially quantified variables makes reasoning over Datalog ∃ un-decidable, in the general case. The results in this paper enable powerful, ye...

This paper faces the problem of answering conjunctive queries over Datalog programs allowing existential quantifiers in rule heads. Such an extension of Datalog is highly expressive, enables easy yet powerful ontology-modelling, but leads to undecidable query answering in general. To overcome undecidability, we first define Shy, a subclass of Datal...

We present L-SME, a system to efficiently identify loosely structured motifs in genome-wide applications. L-SME is innovative in three aspects. Firstly, it handles wider classes of motifs than earlier motif discovery systems, by supporting boxes swaps and skips in the motifs structure as well as various kinds of similarity functions. Secondly, in a...

A data integration system provides transparent access to different data sources by suitably combining their data, and providing the user with a unified view of them, called global schema. However, source data are generally not under the control of the data integration process, thus integrated data may violate global integrity constraints even in pr...

Answer Set Programming is a well-established paradigm of declarative programming in close relationship with other declarative formalisms such as SAT Modulo Theories, Constraint Handling Rules, FO(.), PDDL and many others. Since its first informal editions, ASP systems are compared in the nowadays customary ASP Competition. The Third ASP Competition...

The attention received by query optimization is constantly growing, but efficiently reasoning over natively distributed data is still an open issue. Three main problems must be faced in this context: (i) rules to be processed may contain many atoms and may involve complex joins among them; (ii) the original distribution of input data is a fact and...

In this paper we propose an approach to recommend to a user similar users, resources and social networks in a Social Internetworking Scenario. Our approach presents some interesting novelties with respect to the existing ones. First of all, it operates on a Social Internetworking context and not on a single social network. Moreover, it considers no...

The database community has spent many efforts on the optimization of distributed queries. However, efficiently reasoning over natively distributed data through deductive databases is still an open issue. Three main problems must be faced in this context: (i) rules to be processed may contain many atoms and may involve complex joins among them; (ii)...

An information integration system combines data residing at different sources, providing the user with a unified view of them, called global schema. When some constraints are imposed on the quality of the global data, the integration process becomes difficult and, in some cases, it may be unable to provide consistent results to user queries. The da...

This paper presents a novel approach to provide a user with recommendations about similar users, resources and social networks in a Social Internetworking Scenario. Our approach is characterized by the following main features: (i) differently from most of the approaches previously proposed in the literature, our approach operates on a Social Intern...

DLV is one of the most successful and widely used answer set programming (ASP) systems. It supports a powerful language extending Disjunctive Datalog with many expressive constructs, including aggregates, strong and weak constraints, functions, lists, and sets. The system provides database connectivity offering a simple way for powerful reasoning o...

A data integration system provides transparent access to different data sources by suitably combining their data, and providing the user with a unified view of them, called global schema. However, source data are generally not under the control of the data integration process, thus integrated data may violate global integrity constraints even in pr...