In this paper we study two orthogonal extensions of the classical data mining problem of mining association rules, and show how they naturally interact. The first is the extension from a propositional representation to datalog, and the second is the condensed representation of frequent itemsets by means of Formal Concept Analysis (FCA). We combine the notion of frequent datalog queries with ice...

The Iceberg SemiJoin (ISJ) of two datasets R and S returns the tuples in R which join with at least k tuples of S. The ISJ operator is essential in many practical applications including OLAP, Data Mining and Information Retrieval. In this paper we consider the distributed evaluation of Iceberg SemiJoins, where R and S reside on remote servers. We developed an efficient algorithm which employs B...

Seismometers deployed over a 3 year period on icebergs in the Ross Sea and on the Ross Ice Shelf, Antarctica, reveal that impulsive sources of ocean surface waves are frequent (e.g. ∼200 events per year in the Ross Sea) in the ice-shelf and iceberg-covered environment of coastal Antarctica. The 368 events recorded by our field deployment suggest that these impulsive events are generated by glac...

Iceberg queries have been recently identified as important queries for many applications. These queries can be characterized by their huge input-small output. The iceberg refers to the input, and the tip of it refers to the output. We present an efficient algorithm for computing an important class of iceberg queries. This algorithm uses a focusing technique for the query result using quantiling...

All of the existing (iceberg) cube computation algorithms assume that the data is stored in a single base table, however, in practice, a data warehouse is often organized in a schema of multiple tables, such as star schema and snowflake schema. In terms of both computation time and space, materializing a universal base table by joining multiple tables is often very expensive or even unaffordabl...

Effective pruning is essential for efficient iceberg cube computation. Previous studies have focused on exclusive pruning: regions of a search space that do not satisfy some condition are excluded from computation. In this paper we propose inclusive and anti-pruning. With inclusive pruning, necessary conditions that solutions must satisfy are identified and regions that can not be reached by su...

We introduce the notion of iceberg concept lattices and show their use in Knowledge Discovery in Databases (KDD). Iceberg lattices are a conceptual clustering method, which is well suited for analyzing very large databases. They also serve as a condensed representation of frequent itemsets, as starting point for computing bases of association rules, and as a visualization method for association...