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Efficient Implementation of Large-Scale Multi-Structural Databases

Summary: Multi-structural databases: a unified data model for large-scale, multi-dimensional, hierarchical data, with three optimization-based query types captured in a single framework. Efficient subclass algorithms and a real-time implementation over billions of web documents, aided by random sampling. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9372
Venue
VLDB
Year
2005
Pagerank
5.0935585e-05
Overall Rank
6,370 | 55.69%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
2,154 DIFF: A Relational Interface for Large-Scale Data Explanation 2019 VLDB 9.4208667e-05
6,684 Interesting-Phrase Mining for Ad-Hoc Text Analytics 2010 VLDB 4.9629004e-05
8,104 The Cascading Analysts Algorithm 2018 SIGMOD 4.5851358e-05
12,387 Relaxation in Text Search using Taxonomies 2008 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
11 Implementing Data Cubes Efficiently 1996 SIGMOD 0.0011708144
4,043 What can Hierarchies do for Data Warehouses? 1999 VLDB 6.5015013e-05
4,693 Multi-Structural Databases 2005 PODS 5.9955924e-05
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