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pro vyhledávání: '"Francesco Gullo"'
Publikováno v:
Information Sciences. 402:199-215
Uncertain data clustering has become central in mining data whose observed representation is naturally affected by imprecision, staling, or randomness that is implicit when storing this data from real-word sources. Most existing methods for uncertain
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:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783662448441
ECML/PKDD (3)
ECML/PKDD (3)
The purpose of this technical note is to introduce the problems of similarity detection and summarization in uncertain data. We provide the essential arguments that make the problems relevant to the data-mining and machine-learning community, stating
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http://www.scopus.com/inward/record.url?eid=2-s2.0-84907009764&partnerID=40&md5=c22f33d6414dbc6305830f2f6f3d5fd5
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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:
Lecture Notes in Computer Science ISBN: 9783540879923
SUM
SUM
Uncertain data are usually represented in terms of an uncertainty region over which a probability density function (pdf) is defined. In the context of uncertain data management, there has been a growing interest in clustering uncertain data. In parti
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https://explore.openaire.eu/search/publication?articleId=doi_________::750de51b4b082ba5fbd5c924282c130d
https://doi.org/10.1007/978-3-540-87993-0_19
https://doi.org/10.1007/978-3-540-87993-0_19
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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http://www.scopus.com/inward/record.url?eid=2-s2.0-84863749915&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-84863749915&partnerID=MN8TOARS