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Displaying 1-12 out of 12 total
Finding and Characterizing Communities in Multidimensional Networks
Found in: Social Network Analysis and Mining, International Conference on Advances in
By Michele Berlingerio, Michele Coscia, Fosca Giannotti
Issue Date:July 2011
pp. 490-494
Complex networks have been receiving increasing attention by the scientific community, also due to the availability of massive network data from diverse domains. One problem studied so far in complex network analysis is Community Discovery, i.e. the detect...
 
Towards discovery of eras in social networks
Found in: Data Engineering Workshops, 22nd International Conference on
By Michele Berlingerio, Michele Coscia, Fosca Giannotti, Anna Monreale, Dino Pedreschi
Issue Date:March 2010
pp. 278-281
In the last decades, much research has been devoted in topics related to Social Network Analysis. One important direction in this area is to analyze the temporal evolution of a network. So far, previous approaches analyzed this setting at both the global a...
 
Foundations of Multidimensional Network Analysis
Found in: Social Network Analysis and Mining, International Conference on Advances in
By Michele Berlingerio, Michele Coscia, Fosca Giannotti, Anna Monreale, Dino Pedreschi
Issue Date:July 2011
pp. 485-489
Complex networks have been receiving increasing attention by the scientific community, thanks also to the increasing availability of real-world network data. In the last years, the multidimensional nature of many real world networks has been pointed out, i...
 
Mining HLA Patterns Explaining Liver Diseases
Found in: Computer-Based Medical Systems, IEEE Symposium on
By Michele Berlingerio, Francesco Bonchi, Silvia Chelazzi, Michele Curcio, Fosca Giannotti, Fabrizio Scatena
Issue Date:June 2006
pp. 702-707
HumanLeukocyteAntigens (HLA), also known as histocompatibility antigens, are molecules found on all nucleated cells in the body. Histocompatibility antigens help the immune system to recognize whether or not a cell is foreign to the body, hence the success...
 
SaferCity: A System for Detecting and Analyzing Incidents from Social Media
Found in: 2013 IEEE 13th International Conference on Data Mining Workshops (ICDMW)
By Michele Berlingerio,Francesco Calabrese,Giusy Di Lorenzo,Xiaowen Dong,Yiannis Gkoufas,Dimitrios Mavroeidis
Issue Date:December 2013
pp. 1077-1080
This paper presents a system to identify and characterise public safety related incidents from social media, and enrich the situational awareness that law enforcement entities have on potentially-unreported activities happening in a city. The system is bas...
 
ComeTogether: Discovering Communities of Places in Mobility Data
Found in: 2012 13th IEEE International Conference on Mobile Data Management (MDM)
By Igo Ramalho Brilhante,Michele Berlingerio,Roberto Trasarti,Chiara Renso,Jose Antonio Fernandes de Macedo,Marco Antonio Casanova
Issue Date:July 2012
pp. 268-273
We analyze urban mobility and public places under a new perspective: how can we feature the places in a city based on how people move among them? To answer this question we need to combine places, like points of interest, with mobility information like the...
 
Scalable Link Prediction on Multidimensional Networks
Found in: Data Mining Workshops, International Conference on
By Giulio Rossetti,Michele Berlingerio,Fosca Giannotti
Issue Date:December 2011
pp. 979-986
Complex networks have been receiving increasing attention by the scientific community, also due to the availability of massive network data from diverse domains. One problem largely studied so far is Link Prediction, i.e. the problem of predicting new upco...
 
Learning and Predicting the Evolution of Social Networks
Found in: IEEE Intelligent Systems
By Bjoern Bringmann, Michele Berlingerio, Francesco Bonchi, Arisitdes Gionis
Issue Date:July 2010
pp. 26-35
<p>Graph Evolution Rules help in analyzing the evolution of large networks and can be used to predict the future creation of links among nodes.</p>
 
Mining Clinical Data with a Temporal Dimension: A Case Study
Found in: Bioinformatics and Biomedicine, IEEE International Conference on
By Michele Berlingerio, Francesco Bonchi, Fosca Giannotti, Franco Turini
Issue Date:November 2007
pp. 429-436
Clinical databases store large amounts of information about patients and their medical conditions. Data mining techniques can extract relationships and patterns holding in this wealth of data, and thus be helpful in understand- ing the progression of disea...
 
Time-Annotated Sequences for Medical Data Mining
Found in: Data Mining Workshops, International Conference on
By Michele Berlingerio, Francesco Bonchi, Fosca Giannotti, Franco Turini
Issue Date:October 2007
pp. 133-138
A typical structure of medical data is a sequence of ob- servations of clinical parameters taken at different time mo- ments. In this kind of contexts, the temporal dimension of data is a fundamental variable that should be taken into account in the mining...
 
Finding redundant and complementary communities in multidimensional networks
Found in: Proceedings of the 20th ACM international conference on Information and knowledge management (CIKM '11)
By Fosca Giannotti, Michele Berlingerio, Michele Coscia
Issue Date:October 2011
pp. 2181-2184
Community Discovery in networks is the problem of detecting, for each node, its membership to one of more groups of nodes, the communities, that are densely connected, or highly interactive. We define the community discovery problem in multidimensional net...
     
Temporal mining for interactive workflow data analysis
Found in: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '09)
By Fabio Pinelli, Fosca Giannotti, Michele Berlingerio, Mirco Nanni
Issue Date:June 2009
pp. 1-24
In the past few years there has been an increasing interest in the analysis of process logs. Several proposed techniques, such as workflow mining, are aimed at automatically deriving the underlying workflow models. However, current approaches only pay litt...
     
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