Titlebook: Data Warehousing and Knowledge Discovery; 6th International Co Yahiko Kambayashi,Mukesh Mohania,Wolfram W?? Conference proceedings 2004 Spr

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LUDE

Simulation of Urban Drainage Systemst be transparent. An aggregate retargeting mechanism redirects a query to available aggregate table(s) whenever possible. In this work, we present an aggregate retargeting mechanism that deals with multiple fact table schemas (MFTS), which are composed of many fact tables related by conformed dimens

刻苦讀書

Plasma Chemistry Models of Gas Lasers,t to the constraint that all pre-computed aggregates must fit into storage of a pre-determined size. The target query workload consists of all base and aggregate cells that are stored in a multidimensional array (i.e. cube). These queries are actually range queries pre-defined by users. Due to the h

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locus-ceruleus

R. Días,E. D. Kreimer,R. M. Cecottioundations of data mining has recently been recognized to be even greater concern to data mining..One promising candidate to form a solid basis for data mining is known as inductive databases. The inductive databases are databases with a tight integration to data mining facilities. However, it is no

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https://doi.org/10.1007/978-94-011-2878-0d approach to answering inductive queries in this domain. The approach is based on heuristic search through the space of polynomial equations and can use subsumption and evaluation constraints on polynomial equations. We evaluate this approach on standard regression problems. We finally consider IDB

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David Zhang,Fangmei Chen,Yong Xuytical Processing (OLAP), data mining, and data streams. Ideally, BI research should be driven by industry needs. However, only little information on how BI is used in industry is currently available to the BI research community..This industrial paper presents the experiences that the author has obt

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Space-Efficient Range-Sum Queries in OLAPing sub-linear time update and using minimum space. Furthermore, we study the trade-off between query time and update time. The complexity for query is .(2.) and for updates . on a data cube of .. elements, where ? is a trade-off parameter. Our algorithm improve over previous best known results.

PALMY

From Temporal Rules to Temporal Meta-rulesframework is based on first-order temporal logic and allows the definition of the main temporal data mining notions (event, temporal rule, constraint) in a formal way. The concepts of . and . are fundamentals in the design of algorithms for inferring higher order temporal rules, (called .), from local sets of temporal rules.