Zobrazeno 1 - 8
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pro vyhledávání: '"Francesco Gullo"'
Publikováno v:
Data Mining and Knowledge Discovery. 31:1506-1543
The problem of community detection in a multilayer network can effectively be addressed by aggregating the community structures separately generated for each network layer, in order to infer a consensus solution for the input network. To this purpose
Publikováno v:
Statistical Analysis and Data Mining: The ASA Data Science Journal. 6:116-135
In recent years, there has been a growing interest in clustering uncertain objects. In contrast to traditional, ‘sharp’ data representation models, uncertain objects are modeled as probability distributions defined over uncertainty regions. In th
Publikováno v:
ICDM
A considerable amount of work has been done in data clustering research during the last four decades, and a myriad of methods has been proposed focusing on different data types, proximity functions, cluster representation models, and cluster presenta
Publikováno v:
SIGMOD Conference
Projective Clustering Ensembles (PCE) are a very recent advance in data clustering research which combines the two powerful tools of clustering ensembles and projective clustering.Specifically, PCE enables clustering ensemble methods to handle ensemb
Publikováno v:
ICDM
The increasing demand for dealing with uncertainty in data has led to the development of effective and efficient approaches in the data management and mining contexts. Clustering uncertain data objects has particularly attracted great attention in th
Publikováno v:
ICDM
Projective Clustering Ensembles (PCE) has recently been formulated to solve the problem of deriving a robust projective consensus clustering from an ensemble of projective clustering solutions. PCE is formalized as an optimization problem with either
Publikováno v:
ICDM
In recent years there has been a growing interest in clustering uncertain data. In contrast to traditional, "sharp" data representation models, uncertain data objects can be represented in terms of an uncertainty region over which a probability densi
Autor:
Francesco Gullo, Andrea Tagarelli
Publikováno v:
Scopus-Elsevier
Clustering uncertain data has emerged as a challenging task in uncertain data management and mining. Thanks to a computational complexity advantage over other clustering paradigms, partitional clustering has been particularly studied and a number of
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