http://hdl.handle.net/2117/3488 Sat, 25 May 2013 02:52:01 GMT 2013-05-25T02:52:01Z webmaster.bupc@upc.edu Universitat Politècnica de Catalunya. Servei de Biblioteques i Documentació no http://hdl.handle.net/2117/14824 Title: Frequent sets, sequences and taxonomies: new efficient algorithmic proposals Authors: Baixeries i Juvillà, Jaume; Casas Garriga, Gemma; Balcázar Navarro, José Luis Abstract: We describe efficient algorithmic proposals to approach three fundamental problems in data mining: association rules, episodes in sequences, and generalized association rules over hierarchical taxonomies. The association rule discovery problem aims at identifying frequent itemsets in a database and then forming conditional implication rules among them. For this association task, we will introduce a new algorithmic proposal to reduce substantially the number of processed transactions. The resulting algorithm, called Ready-and-Go, is used to discover frequent sets efficiently. Then, for the discovery of patterns in sequences of events in ordered collections of data, we propose to apply the appropiate variant of that algorithm, and additionally we introduce a new framework for the formalization of the concept of intereseting episodes. Finally, we adapt our algorithm to the generalization of the frequent sets problem where data comes organized in taxonomic hierarchies, and here additionally we contribute with a new heuristic that, under certain natural conditions, improves the performance. Thu, 26 Jan 2012 10:47:30 GMT http://hdl.handle.net/2117/14824 2012-01-26T10:47:30Z Baixeries i Juvillà, Jaume; Casas Garriga, Gemma; Balcázar Navarro, José Luis no We describe efficient algorithmic proposals to approach three fundamental problems in data mining: association rules, episodes in sequences, and generalized association rules over hierarchical taxonomies. The association rule discovery problem aims at identifying frequent itemsets in a database and then forming conditional implication rules among them. For this association task, we will introduce a new algorithmic proposal to reduce substantially the number of processed transactions. The resulting algorithm, called Ready-and-Go, is used to discover frequent sets efficiently. Then, for the discovery of patterns in sequences of events in ordered collections of data, we propose to apply the appropiate variant of that algorithm, and additionally we introduce a new framework for the formalization of the concept of intereseting episodes. Finally, we adapt our algorithm to the generalization of the frequent sets problem where data comes organized in taxonomic hierarchies, and here additionally we contribute with a new heuristic that, under certain natural conditions, improves the performance. http://hdl.handle.net/2117/11061 Title: An integer linear programming representation for data-center power-aware management Authors: Berral García, Josep Lluís; Gavaldà Mestre, Ricard; Torres Viñals, Jordi Abstract: This work exposes how to represent a grid data-center based scheduling problem, taking the advantages of the virtualization and consolidation techniques, as a linear integer programming problem including all three mentioned factors. Although being integer linear programming (ILP) a computationally hard problem, specifying correctly its constraints and optimization function can contribute to find integer optimal solutions in relative short time. So ILP solutions can help designers and system managers not only to apply them to schedulers but also to create new heuristics and holistic functions that approximate well to the optimal solutions in a quicker way. Mon, 17 Jan 2011 11:21:12 GMT http://hdl.handle.net/2117/11061 2011-01-17T11:21:12Z Berral García, Josep Lluís; Gavaldà Mestre, Ricard; Torres Viñals, Jordi no This work exposes how to represent a grid data-center based scheduling problem, taking the advantages of the virtualization and consolidation techniques, as a linear integer programming problem including all three mentioned factors. Although being integer linear programming (ILP) a computationally hard problem, specifying correctly its constraints and optimization function can contribute to find integer optimal solutions in relative short time. So ILP solutions can help designers and system managers not only to apply them to schedulers but also to create new heuristics and holistic functions that approximate well to the optimal solutions in a quicker way.