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 Michelangelo Ceci

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Average citations per article0.75
Citation Count21
Publication count28
Publication years2005-2018
Available for download3
Average downloads per article226.00
Downloads (cumulative)678
Downloads (12 Months)137
Downloads (6 Weeks)19
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28 results found Export Results: bibtexendnoteacmrefcsv

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1
January 2018 Information Sciences: an International Journal: Volume 425 Issue C, January 2018
Publisher: Elsevier Science Inc.
Bibliometrics:
Citation Count: 0

Heterogeneous information networks consist of different types of objects and links. They can be found in several social, economic and scientific fields, ranging from the Internet to social sciences, including biology, epidemiology, geography, finance and many others. In the literature, several clustering and classification algorithms have been proposed which work ...
Keywords: Multi-type classification, Heterogeneous networks, Multi-type clustering

2
December 2017 Journal of Intelligent Information Systems: Volume 49 Issue 3, December 2017
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 0

In many real-life problems, obtaining labelled data can be a very expensive and laborious task, while unlabeled data can be abundant. The availability of labeled data can seriously limit the performance of supervised learning methods. Here, we propose a semi-supervised classification tree induction algorithm that can exploit both the labelled ...
Keywords: Decision trees, Semi-supervised learning, Binary classification, Multi-class classification, Random forests

3
May 2017 Knowledge-Based Systems: Volume 123 Issue C, May 2017
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 0

Semi-supervised learning (SSL) aims to use unlabeled data as an additional source of information in order to improve upon the performance of supervised learning methods. The availability of labeled data is often limited due to the expensive and/or tedious annotation process, while unlabeled data could be easily available in large ...
Keywords: Multi-target regression, Semi-supervised learning, Predictive clustering trees, Random forests, Reliability of predictions, Self-training

4
August 2016 Journal of Intelligent Information Systems: Volume 47 Issue 1, August 2016
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 0

Keywords: Complex pattern discovery, Complex data, Data mining

5
August 2016 Knowledge and Information Systems: Volume 48 Issue 2, August 2016
Publisher: Springer-Verlag New York, Inc.
Bibliometrics:
Citation Count: 0

Sequential pattern mining is a computationally challenging task since algorithms have to generate and/or test a combinatorially explosive number of intermediate subsequences. In order to reduce complexity, some researchers focus on the task of mining closed sequential patterns. This not only results in increased efficiency, but also provides a way ...
Keywords: Closed sequences, Data mining, Itemset, Sequential pattern mining

6 published by ACM
July 2015 IDEAS '15: Proceedings of the 19th International Database Engineering & Applications Symposium
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 9,   Downloads (12 Months): 32,   Downloads (Overall): 140

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Predicting the output power of renewable energy production plants distributed on a wide territory is a really valuable goal, both for marketing and energy management purposes. Vi-POC (Virtual Power Operating Center) project aims at designing and implementing a prototype which is able to achieve this goal. Due to the heterogeneity ...

7
June 2015 Journal of Intelligent Information Systems: Volume 44 Issue 3, June 2015
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 2

In traditional OLAP systems, roll-up and drill-down operations over data cubes exploit fixed hierarchies defined on discrete attributes, which play the roles of dimensions, and operate along them. New emerging application scenarios, such as sensor networks, have stimulated research on OLAP systems, where even continuous attributes are considered as dimensions ...
Keywords: Hierarchical clustering, OLAP, OLAP on continuous domains

8
April 2015
Bibliometrics:
Citation Count: 0

This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2014, held in conjunction with ECML-PKDD 2014 in Nancy, France, in September 2014. The 13 revised full papers presented were carefully reviewed and selected from numerous submissions. They illustrate ...

9
February 2015 Neurocomputing: Volume 150 Issue PA, February 2015
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 2

Networks are data structures more and more frequently used for modeling interactions in social and biological phenomena, as well as between various types of devices, tools and machines. They can be either static or dynamic, dependently on whether the modeled interactions are fixed or changeable over time. Static networks have ...
Keywords: Discovery of change patterns, Change mining in networked data, Discovery of evolution chains, Evolving networks

10
September 2014 NFMCP'14: Proceedings of the 3rd International Conference on New Frontiers in Mining Complex Patterns
Publisher: Springer
Bibliometrics:
Citation Count: 1

The most common machine learning approach is supervised learning, which uses labeled data for building predictive models. However, in many practical problems, the availability of annotated data is limited due to the expensive, tedious and time-consuming annotation procedure. At the same, unlabeled data can be easily available in large amounts. ...
Keywords: PCTs, ensembles, multi-target, self-training, multi-output, multivariate, semi-supervised learning, structured outputs, regression

11
September 2014 ECMLPKDD'14: Proceedings of the 2014th European Conference on Machine Learning and Knowledge Discovery in Databases - Volume Part III
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

Network reconstruction from data is a data mining task which is receiving a significant attention due to its applicability in several domains. For example, it can be applied in social network analysis, where the goal is to identify connections among users and, thus, sub-communities. Another example can be found in ...

12 published by ACM
September 2014 Journal on Computing and Cultural Heritage (JOCCH): Volume 7 Issue 4, February 2015
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 9,   Downloads (12 Months): 84,   Downloads (Overall): 413

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Studying Greek and Latin cultural heritage has always been considered essential to the understanding of important aspects of the roots of current European societies. However, only a small fraction of the total production of texts from ancient Greece and Rome has survived up to the present, leaving many gaps in ...
Keywords: evolution discovery, Epigraphy, novelty pattern mining

13
July 2014
Bibliometrics:
Citation Count: 0

This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2013, held in conjunction with ECML/PKDD 2013 in Prague, Czech Republic, in September 2013. The 16 revised full papers were carefully reviewed and selected from numerous submissions. The papers ...

14 published by ACM
July 2014 IDEAS '14: Proceedings of the 18th International Database Engineering & Applications Symposium
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 1,   Downloads (12 Months): 21,   Downloads (Overall): 125

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The problem of accurately predicting the energy production from renewable sources has recently received an increasing attention from both the industrial and the research communities. It presents several challenges, such as facing with the rate data are provided by sensors, the heterogeneity of the data collected, power plants efficiency, as ...

15
July 2014 Fundamenta Informaticae: Volume 129 Issue 3, July 2014
Publisher: IOS Press
Bibliometrics:
Citation Count: 0

Multi-Relational Data Mining MRDM refers to the process of discovering implicit, previously unknown and potentially useful information from data scattered in multiple tables of a relational database. Following the mainstream of MRDM research, we tackle the regression where the goal is to examine samples of past experience with known continuous ...
Keywords: Data Mining, Regression, Relational Model Trees, Lookahead In Model Tree Induction, Mining Methods And Algorithms, Relational Dbms Coupling

16
September 2012 NFMCP'12: Proceedings of the First International Conference on New Frontiers in Mining Complex Patterns
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

Most of the works on learning from networked data assume that the network is static. In this paper we consider a different scenario, where the network is dynamic, i.e. nodes/relationships can be added or removed and relationships can change in their type over time. We assume that the "core" of ...

17
September 2012 NFMCP'12: Proceedings of the First international conference on New Frontiers in Mining Complex Patterns
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 4

Most of the works on learning from networked data assume that the network is static. In this paper we consider a different scenario, where the network is dynamic, i.e. nodes/relationships can be added or removed and relationships can change in their type over time. We assume that the "core" of ...

18
September 2012 Data Mining and Knowledge Discovery: Volume 25 Issue 2, September 2012
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 8

Network data describe entities represented by nodes, which may be connected with (related to) each other by edges. Many network datasets are characterized by a form of autocorrelation, where the value of a variable at a given node depends on the values of variables at the nodes it is connected ...
Keywords: Predictive clustering trees, Regression inference, Network data, Autocorrelation

19
August 2012 ECAI'12: Proceedings of the 20th European Conference on Artificial Intelligence
Publisher: IOS Press
Bibliometrics:
Citation Count: 0

microRNAs (miRNAs) are an important class of regulatory factors controlling gene expressions at post-transcriptional level. Studies on interactions between different miRNAs and their target genes are of utmost importance to understand the role of miRNAs in the control of biological processes. This paper contributes to these studies by proposing a ...

20
July 2012 MLDM'12: Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 1

In recent years, improvement in ubiquitous technologies and sensor networks have motivated the application of data mining techniques to network organized data. Network data describe entities represented by nodes, which may be connected with (related to) each other by edges. Many network datasets are characterized by a form of autocorrelation ...



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