Efficient Mining of Frequent Closures with Precedence Links and Associated Generators
| Autor: | Szathmary, Laszlo, Valtchev, Petko, Napoli, Amedeo |
|---|---|
| Přispěvatelé: | Knowledge representation, reasonning (ORPAILLEUR), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Lorraine (INPL)-Université Nancy 2-Université Henri Poincaré - Nancy 1 (UHP)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Lorraine (INPL)-Université Nancy 2-Université Henri Poincaré - Nancy 1 (UHP), Laboratory for Research on Technology for ECommerce (LATECE Laboratory - UQAM Montreal), Université du Québec à Montréal = University of Québec in Montréal (UQAM), INRIA, Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2008 |
| Předmět: |
ACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.3: Information Search and Retrieval
motifs fermés algorithm data mining itemset search association rule bases closed itemsets generators concept lattice iceberg lattice treillis de concepts treillis iceberg [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS] motifs fréquents bases algorithmes pour la fouille de données motifs générateurs règles d'association |
| Zdroj: | [Research Report] RR-6657, INRIA. 2008, pp.58 |
| Popis: | The effective construction of many association rule bases require the computation of frequent closures, generators, and precedence links between closures. However, these tasks are rarely combined, and no scalable algorithm exists at present for their joint computation. We propose here a method that solves this challenging problem in two separated steps. First, we introduce a new algorithm called Touch for finding frequent closed itemsets (FCIs) and their generators (FGs). Touch applies depth-first traversal, and experimental results indicate that this algorithm is highly efficient and outperforms its levelwise competitors. Second, we propose another algorithm called Snow for extracting efficiently the precedence from the output of Touch. To do so, we apply hypergraph theory. Snow is a generic algorithm that can be used with any FCI/FG-miner. The two algorithms, Touch and Snow, provide a complete solution for constructing iceberg lattices. Furthermore, due to their modular design, parts of the algorithms can also be used independently. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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