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EnglishWe present a survey of the most important algorithms that have been pro- posed in the context of the Frequent Itemset Mining. We start with an introduction and overview of basic sequential algorithms, and then discuss and compare differ- ent parallel approaches based on shared-memory, message-passing, map-reduce and the use of GPU accelerators. Even though our survey certainly is not exhaustive, it covers essential reference material, since we believe that an attempt to cover every- thing will instead fail to convey any useful information to the interested readers. Our hope is that this work will help interested researchers and practitioners, in particular those coming from a business-oriented background, quickly enabling them to de- velop their understanding of an area likely to play an ever more significant role in coming years.
| Titolo: | Frequent Itemset Mining | |
| Autori: | ||
| Data di pubblicazione: | 2019 | |
| Abstract: | We present a survey of the most important algorithms that have been pro- posed in the context of the Frequent Itemset Mining. We start with an introduction and overview of basic sequential algorithms, and then discuss and compare differ- ent parallel approaches based on shared-memory, message-passing, map-reduce and the use of GPU accelerators. Even though our survey certainly is not exhaustive, it covers essential reference material, since we believe that an attempt to cover every- thing will instead fail to convey any useful information to the interested readers. Our hope is that this work will help interested researchers and practitioners, in particular those coming from a business-oriented background, quickly enabling them to de- velop their understanding of an area likely to play an ever more significant role in coming years. | |
| Handle: | http://hdl.handle.net/11587/432025 | |
| ISBN: | 978-3-030-06221-7 978-3-030-06222-4 | |
| Appare nelle tipologie: | Capitolo di Libro |
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