Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Nagender Parimi"'
Autor:
Jeevan Pathuri, Nilanjana De, Paolo Palmerini, Nagender Parimi, Benjarath Phoophakdee, Feng Gao, Mohammed J. Zaki, Joe Urban
Publikováno v:
Constraint-Based Mining and Inductive Databases ISBN: 9783540313311
Constraint-Based Mining and Inductive Databases
Constraint-Based Mining and Inductive Databases
Frequent Pattern Mining (FPM) is a very powerful paradigm for mining informative and useful patterns in massive, complex datasets. In this paper we propose the Data Mining Template Library, a collection of generic containers and algorithms for data m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57a0615be0208ff6be76d5308e236de2
https://doi.org/10.1007/11615576_17
https://doi.org/10.1007/11615576_17
Autor:
Feng Gao, Saeed Salem, Nilanjana De, Mohammad Al Hasan, Nagender Parimi, Benjarath Phoophakdee, Mohammed J. Zaki, Joe Urban, Vineet Chaoji
Publikováno v:
Formal Concept Analysis ISBN: 9783540245254
ICFCA
Scopus-Elsevier
ICFCA
Scopus-Elsevier
Frequent Pattern Mining (FPM) is a very powerful paradigm for mining informative and useful patterns in massive, complex datasets. In this paper we propose the Data Mining Template Library, a collection of generic containers and algorithms for FPM, a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8b1ec28b0bcc556de29535d43f6a4bc
https://doi.org/10.1007/978-3-540-32262-7_1
https://doi.org/10.1007/978-3-540-32262-7_1
Autor:
Benjarath Phoophakdee, Mohammed J. Zaki, Nilanjana De, Joe Urban Vineet Chaoji, Saeed Salem, Mohammad Al Hasan, Feng Gao, Nagender Parimi
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783540305064
PReMI
PReMI
Frequent Pattern Mining (FPM) is a very powerful paradigm which encompasses an entire class of data mining tasks. The specific tasks encompassed by FPM include the mining of increasingly complex and informative patterns, in complex structured and uns
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0dec9da0c8542941e6d03729a14159b
https://doi.org/10.1007/11590316_12
https://doi.org/10.1007/11590316_12